Running model: base_model w/opt: SGD
Train on 1712 samples, validate on 428 samples
Epoch 1/50
Epoch 00000: val_loss improved from inf to 0.01482, saving model to ./model/SGD_model.weights.best.hdf5
3s - loss: 0.0809 - acc: 0.1577 - mean_squared_error: 0.0809 - val_loss: 0.0148 - val_acc: 0.6776 - val_mean_squared_error: 0.0148
Epoch 2/50
Epoch 00001: val_loss improved from 0.01482 to 0.01027, saving model to ./model/SGD_model.weights.best.hdf5
2s - loss: 0.0282 - acc: 0.3306 - mean_squared_error: 0.0282 - val_loss: 0.0103 - val_acc: 0.6963 - val_mean_squared_error: 0.0103
Epoch 3/50
Epoch 00002: val_loss improved from 0.01027 to 0.00928, saving model to ./model/SGD_model.weights.best.hdf5
2s - loss: 0.0250 - acc: 0.3680 - mean_squared_error: 0.0250 - val_loss: 0.0093 - val_acc: 0.6939 - val_mean_squared_error: 0.0093
Epoch 4/50
Epoch 00003: val_loss improved from 0.00928 to 0.00902, saving model to ./model/SGD_model.weights.best.hdf5
2s - loss: 0.0233 - acc: 0.3879 - mean_squared_error: 0.0233 - val_loss: 0.0090 - val_acc: 0.6963 - val_mean_squared_error: 0.0090
Epoch 5/50
Epoch 00004: val_loss improved from 0.00902 to 0.00866, saving model to ./model/SGD_model.weights.best.hdf5
2s - loss: 0.0218 - acc: 0.4182 - mean_squared_error: 0.0218 - val_loss: 0.0087 - val_acc: 0.6963 - val_mean_squared_error: 0.0087
Epoch 6/50
Epoch 00005: val_loss improved from 0.00866 to 0.00802, saving model to ./model/SGD_model.weights.best.hdf5
2s - loss: 0.0207 - acc: 0.4036 - mean_squared_error: 0.0207 - val_loss: 0.0080 - val_acc: 0.6963 - val_mean_squared_error: 0.0080
Epoch 7/50
Epoch 00006: val_loss improved from 0.00802 to 0.00776, saving model to ./model/SGD_model.weights.best.hdf5
2s - loss: 0.0195 - acc: 0.4206 - mean_squared_error: 0.0195 - val_loss: 0.0078 - val_acc: 0.6963 - val_mean_squared_error: 0.0078
Epoch 8/50
Epoch 00007: val_loss improved from 0.00776 to 0.00757, saving model to ./model/SGD_model.weights.best.hdf5
2s - loss: 0.0187 - acc: 0.4416 - mean_squared_error: 0.0187 - val_loss: 0.0076 - val_acc: 0.6963 - val_mean_squared_error: 0.0076
Epoch 9/50
Epoch 00008: val_loss improved from 0.00757 to 0.00711, saving model to ./model/SGD_model.weights.best.hdf5
2s - loss: 0.0178 - acc: 0.4550 - mean_squared_error: 0.0178 - val_loss: 0.0071 - val_acc: 0.6963 - val_mean_squared_error: 0.0071
Epoch 10/50
Epoch 00009: val_loss improved from 0.00711 to 0.00699, saving model to ./model/SGD_model.weights.best.hdf5
2s - loss: 0.0173 - acc: 0.4644 - mean_squared_error: 0.0173 - val_loss: 0.0070 - val_acc: 0.6963 - val_mean_squared_error: 0.0070
Epoch 11/50
Epoch 00010: val_loss did not improve
2s - loss: 0.0168 - acc: 0.4428 - mean_squared_error: 0.0168 - val_loss: 0.0070 - val_acc: 0.6963 - val_mean_squared_error: 0.0070
Epoch 12/50
Epoch 00011: val_loss improved from 0.00699 to 0.00694, saving model to ./model/SGD_model.weights.best.hdf5
2s - loss: 0.0162 - acc: 0.4591 - mean_squared_error: 0.0162 - val_loss: 0.0069 - val_acc: 0.6963 - val_mean_squared_error: 0.0069
Epoch 13/50
Epoch 00012: val_loss improved from 0.00694 to 0.00646, saving model to ./model/SGD_model.weights.best.hdf5
2s - loss: 0.0157 - acc: 0.4620 - mean_squared_error: 0.0157 - val_loss: 0.0065 - val_acc: 0.6963 - val_mean_squared_error: 0.0065
Epoch 14/50
Epoch 00013: val_loss did not improve
2s - loss: 0.0156 - acc: 0.4743 - mean_squared_error: 0.0156 - val_loss: 0.0066 - val_acc: 0.6963 - val_mean_squared_error: 0.0066
Epoch 15/50
Epoch 00014: val_loss improved from 0.00646 to 0.00629, saving model to ./model/SGD_model.weights.best.hdf5
2s - loss: 0.0149 - acc: 0.4778 - mean_squared_error: 0.0149 - val_loss: 0.0063 - val_acc: 0.6963 - val_mean_squared_error: 0.0063
Epoch 16/50
Epoch 00015: val_loss improved from 0.00629 to 0.00602, saving model to ./model/SGD_model.weights.best.hdf5
2s - loss: 0.0146 - acc: 0.4842 - mean_squared_error: 0.0146 - val_loss: 0.0060 - val_acc: 0.6963 - val_mean_squared_error: 0.0060
Epoch 17/50
Epoch 00016: val_loss improved from 0.00602 to 0.00598, saving model to ./model/SGD_model.weights.best.hdf5
2s - loss: 0.0142 - acc: 0.4655 - mean_squared_error: 0.0142 - val_loss: 0.0060 - val_acc: 0.6963 - val_mean_squared_error: 0.0060
Epoch 18/50
Epoch 00017: val_loss did not improve
2s - loss: 0.0139 - acc: 0.4994 - mean_squared_error: 0.0139 - val_loss: 0.0060 - val_acc: 0.6963 - val_mean_squared_error: 0.0060
Epoch 19/50
Epoch 00018: val_loss improved from 0.00598 to 0.00584, saving model to ./model/SGD_model.weights.best.hdf5
2s - loss: 0.0138 - acc: 0.5187 - mean_squared_error: 0.0138 - val_loss: 0.0058 - val_acc: 0.6963 - val_mean_squared_error: 0.0058
Epoch 20/50
Epoch 00019: val_loss improved from 0.00584 to 0.00569, saving model to ./model/SGD_model.weights.best.hdf5
2s - loss: 0.0135 - acc: 0.5012 - mean_squared_error: 0.0135 - val_loss: 0.0057 - val_acc: 0.6963 - val_mean_squared_error: 0.0057
Epoch 21/50
Epoch 00020: val_loss did not improve
2s - loss: 0.0132 - acc: 0.5117 - mean_squared_error: 0.0132 - val_loss: 0.0059 - val_acc: 0.6963 - val_mean_squared_error: 0.0059
Epoch 22/50
Epoch 00021: val_loss improved from 0.00569 to 0.00544, saving model to ./model/SGD_model.weights.best.hdf5
2s - loss: 0.0131 - acc: 0.5029 - mean_squared_error: 0.0131 - val_loss: 0.0054 - val_acc: 0.6963 - val_mean_squared_error: 0.0054
Epoch 23/50
Epoch 00022: val_loss did not improve
2s - loss: 0.0127 - acc: 0.4907 - mean_squared_error: 0.0127 - val_loss: 0.0055 - val_acc: 0.6963 - val_mean_squared_error: 0.0055
Epoch 24/50
Epoch 00023: val_loss did not improve
2s - loss: 0.0124 - acc: 0.5374 - mean_squared_error: 0.0124 - val_loss: 0.0055 - val_acc: 0.6963 - val_mean_squared_error: 0.0055
Epoch 25/50
Epoch 00024: val_loss improved from 0.00544 to 0.00542, saving model to ./model/SGD_model.weights.best.hdf5
2s - loss: 0.0124 - acc: 0.5134 - mean_squared_error: 0.0124 - val_loss: 0.0054 - val_acc: 0.6963 - val_mean_squared_error: 0.0054
Epoch 26/50
Epoch 00025: val_loss improved from 0.00542 to 0.00530, saving model to ./model/SGD_model.weights.best.hdf5
2s - loss: 0.0122 - acc: 0.5076 - mean_squared_error: 0.0122 - val_loss: 0.0053 - val_acc: 0.6963 - val_mean_squared_error: 0.0053
Epoch 27/50
Epoch 00026: val_loss improved from 0.00530 to 0.00518, saving model to ./model/SGD_model.weights.best.hdf5
2s - loss: 0.0120 - acc: 0.5134 - mean_squared_error: 0.0120 - val_loss: 0.0052 - val_acc: 0.6963 - val_mean_squared_error: 0.0052
Epoch 28/50
Epoch 00027: val_loss did not improve
2s - loss: 0.0119 - acc: 0.5181 - mean_squared_error: 0.0119 - val_loss: 0.0053 - val_acc: 0.6963 - val_mean_squared_error: 0.0053
Epoch 29/50
Epoch 00028: val_loss improved from 0.00518 to 0.00517, saving model to ./model/SGD_model.weights.best.hdf5
2s - loss: 0.0119 - acc: 0.5082 - mean_squared_error: 0.0119 - val_loss: 0.0052 - val_acc: 0.6963 - val_mean_squared_error: 0.0052
Epoch 30/50
Epoch 00029: val_loss did not improve
2s - loss: 0.0117 - acc: 0.5146 - mean_squared_error: 0.0117 - val_loss: 0.0052 - val_acc: 0.6963 - val_mean_squared_error: 0.0052
Epoch 31/50
Epoch 00030: val_loss did not improve
2s - loss: 0.0115 - acc: 0.5152 - mean_squared_error: 0.0115 - val_loss: 0.0053 - val_acc: 0.6963 - val_mean_squared_error: 0.0053
Epoch 32/50
Epoch 00031: val_loss improved from 0.00517 to 0.00504, saving model to ./model/SGD_model.weights.best.hdf5
2s - loss: 0.0115 - acc: 0.5473 - mean_squared_error: 0.0115 - val_loss: 0.0050 - val_acc: 0.6963 - val_mean_squared_error: 0.0050
Epoch 33/50
Epoch 00032: val_loss did not improve
2s - loss: 0.0112 - acc: 0.5164 - mean_squared_error: 0.0112 - val_loss: 0.0051 - val_acc: 0.6963 - val_mean_squared_error: 0.0051
Epoch 34/50
Epoch 00033: val_loss improved from 0.00504 to 0.00499, saving model to ./model/SGD_model.weights.best.hdf5
2s - loss: 0.0111 - acc: 0.5456 - mean_squared_error: 0.0111 - val_loss: 0.0050 - val_acc: 0.6963 - val_mean_squared_error: 0.0050
Epoch 35/50
Epoch 00034: val_loss did not improve
2s - loss: 0.0111 - acc: 0.5082 - mean_squared_error: 0.0111 - val_loss: 0.0050 - val_acc: 0.6963 - val_mean_squared_error: 0.0050
Epoch 36/50
Epoch 00035: val_loss did not improve
2s - loss: 0.0109 - acc: 0.5146 - mean_squared_error: 0.0109 - val_loss: 0.0051 - val_acc: 0.6963 - val_mean_squared_error: 0.0051
Epoch 37/50
Epoch 00036: val_loss improved from 0.00499 to 0.00491, saving model to ./model/SGD_model.weights.best.hdf5
2s - loss: 0.0108 - acc: 0.5315 - mean_squared_error: 0.0108 - val_loss: 0.0049 - val_acc: 0.6963 - val_mean_squared_error: 0.0049
Epoch 38/50
Epoch 00037: val_loss improved from 0.00491 to 0.00489, saving model to ./model/SGD_model.weights.best.hdf5
2s - loss: 0.0108 - acc: 0.5345 - mean_squared_error: 0.0108 - val_loss: 0.0049 - val_acc: 0.6963 - val_mean_squared_error: 0.0049
Epoch 39/50
Epoch 00038: val_loss did not improve
2s - loss: 0.0105 - acc: 0.5386 - mean_squared_error: 0.0105 - val_loss: 0.0050 - val_acc: 0.6963 - val_mean_squared_error: 0.0050
Epoch 40/50
Epoch 00039: val_loss did not improve
2s - loss: 0.0106 - acc: 0.5193 - mean_squared_error: 0.0106 - val_loss: 0.0049 - val_acc: 0.6963 - val_mean_squared_error: 0.0049
Epoch 41/50
Epoch 00040: val_loss improved from 0.00489 to 0.00479, saving model to ./model/SGD_model.weights.best.hdf5
2s - loss: 0.0106 - acc: 0.5561 - mean_squared_error: 0.0106 - val_loss: 0.0048 - val_acc: 0.6963 - val_mean_squared_error: 0.0048
Epoch 42/50
Epoch 00041: val_loss improved from 0.00479 to 0.00475, saving model to ./model/SGD_model.weights.best.hdf5
2s - loss: 0.0103 - acc: 0.5543 - mean_squared_error: 0.0103 - val_loss: 0.0048 - val_acc: 0.6963 - val_mean_squared_error: 0.0048
Epoch 43/50
Epoch 00042: val_loss did not improve
2s - loss: 0.0104 - acc: 0.5549 - mean_squared_error: 0.0104 - val_loss: 0.0049 - val_acc: 0.6963 - val_mean_squared_error: 0.0049
Epoch 44/50
Epoch 00043: val_loss did not improve
2s - loss: 0.0103 - acc: 0.5444 - mean_squared_error: 0.0103 - val_loss: 0.0049 - val_acc: 0.6963 - val_mean_squared_error: 0.0049
Epoch 45/50
Epoch 00044: val_loss did not improve
2s - loss: 0.0101 - acc: 0.5409 - mean_squared_error: 0.0101 - val_loss: 0.0049 - val_acc: 0.6963 - val_mean_squared_error: 0.0049
Epoch 46/50
Epoch 00045: val_loss did not improve
2s - loss: 0.0101 - acc: 0.5444 - mean_squared_error: 0.0101 - val_loss: 0.0048 - val_acc: 0.6963 - val_mean_squared_error: 0.0048
Epoch 47/50
Epoch 00046: val_loss did not improve
2s - loss: 0.0101 - acc: 0.5461 - mean_squared_error: 0.0101 - val_loss: 0.0048 - val_acc: 0.6963 - val_mean_squared_error: 0.0048
Epoch 48/50
Epoch 00047: val_loss did not improve
2s - loss: 0.0101 - acc: 0.5485 - mean_squared_error: 0.0101 - val_loss: 0.0048 - val_acc: 0.6963 - val_mean_squared_error: 0.0048
Epoch 49/50
Epoch 00048: val_loss did not improve
2s - loss: 0.0100 - acc: 0.5502 - mean_squared_error: 0.0100 - val_loss: 0.0049 - val_acc: 0.6963 - val_mean_squared_error: 0.0049
Epoch 50/50
Epoch 00049: val_loss did not improve
2s - loss: 0.0098 - acc: 0.5660 - mean_squared_error: 0.0098 - val_loss: 0.0049 - val_acc: 0.6963 - val_mean_squared_error: 0.0049
Running model: base_model w/opt: RMSprop
Train on 1712 samples, validate on 428 samples
Epoch 1/50
Epoch 00000: val_loss improved from inf to 0.00879, saving model to ./model/RMSprop_model.weights.best.hdf5
3s - loss: 0.2576 - acc: 0.3697 - mean_squared_error: 0.2576 - val_loss: 0.0088 - val_acc: 0.5818 - val_mean_squared_error: 0.0088
Epoch 2/50
Epoch 00001: val_loss improved from 0.00879 to 0.00551, saving model to ./model/RMSprop_model.weights.best.hdf5
2s - loss: 0.0242 - acc: 0.4655 - mean_squared_error: 0.0242 - val_loss: 0.0055 - val_acc: 0.6963 - val_mean_squared_error: 0.0055
Epoch 3/50
Epoch 00002: val_loss did not improve
2s - loss: 0.0127 - acc: 0.5245 - mean_squared_error: 0.0127 - val_loss: 0.0067 - val_acc: 0.6963 - val_mean_squared_error: 0.0067
Epoch 4/50
Epoch 00003: val_loss did not improve
2s - loss: 0.0092 - acc: 0.6092 - mean_squared_error: 0.0092 - val_loss: 0.0074 - val_acc: 0.6963 - val_mean_squared_error: 0.0074
Epoch 5/50
Epoch 00004: val_loss improved from 0.00551 to 0.00418, saving model to ./model/RMSprop_model.weights.best.hdf5
2s - loss: 0.0078 - acc: 0.6244 - mean_squared_error: 0.0078 - val_loss: 0.0042 - val_acc: 0.6963 - val_mean_squared_error: 0.0042
Epoch 6/50
Epoch 00005: val_loss did not improve
2s - loss: 0.0065 - acc: 0.6636 - mean_squared_error: 0.0065 - val_loss: 0.0064 - val_acc: 0.6916 - val_mean_squared_error: 0.0064
Epoch 7/50
Epoch 00006: val_loss did not improve
2s - loss: 0.0060 - acc: 0.6711 - mean_squared_error: 0.0060 - val_loss: 0.0055 - val_acc: 0.6916 - val_mean_squared_error: 0.0055
Epoch 8/50
Epoch 00007: val_loss improved from 0.00418 to 0.00348, saving model to ./model/RMSprop_model.weights.best.hdf5
2s - loss: 0.0051 - acc: 0.6869 - mean_squared_error: 0.0051 - val_loss: 0.0035 - val_acc: 0.6939 - val_mean_squared_error: 0.0035
Epoch 9/50
Epoch 00008: val_loss improved from 0.00348 to 0.00262, saving model to ./model/RMSprop_model.weights.best.hdf5
2s - loss: 0.0048 - acc: 0.6875 - mean_squared_error: 0.0048 - val_loss: 0.0026 - val_acc: 0.7126 - val_mean_squared_error: 0.0026
Epoch 10/50
Epoch 00009: val_loss did not improve
2s - loss: 0.0045 - acc: 0.6963 - mean_squared_error: 0.0045 - val_loss: 0.0063 - val_acc: 0.7220 - val_mean_squared_error: 0.0063
Epoch 11/50
Epoch 00010: val_loss did not improve
2s - loss: 0.0039 - acc: 0.6974 - mean_squared_error: 0.0039 - val_loss: 0.0030 - val_acc: 0.7173 - val_mean_squared_error: 0.0030
Epoch 12/50
Epoch 00011: val_loss improved from 0.00262 to 0.00202, saving model to ./model/RMSprop_model.weights.best.hdf5
2s - loss: 0.0037 - acc: 0.7114 - mean_squared_error: 0.0037 - val_loss: 0.0020 - val_acc: 0.7196 - val_mean_squared_error: 0.0020
Epoch 13/50
Epoch 00012: val_loss did not improve
2s - loss: 0.0034 - acc: 0.7225 - mean_squared_error: 0.0034 - val_loss: 0.0021 - val_acc: 0.7196 - val_mean_squared_error: 0.0021
Epoch 14/50
Epoch 00013: val_loss improved from 0.00202 to 0.00188, saving model to ./model/RMSprop_model.weights.best.hdf5
2s - loss: 0.0032 - acc: 0.7202 - mean_squared_error: 0.0032 - val_loss: 0.0019 - val_acc: 0.7360 - val_mean_squared_error: 0.0019
Epoch 15/50
Epoch 00014: val_loss did not improve
2s - loss: 0.0029 - acc: 0.7266 - mean_squared_error: 0.0029 - val_loss: 0.0022 - val_acc: 0.7103 - val_mean_squared_error: 0.0022
Epoch 16/50
Epoch 00015: val_loss did not improve
2s - loss: 0.0027 - acc: 0.7336 - mean_squared_error: 0.0027 - val_loss: 0.0025 - val_acc: 0.7407 - val_mean_squared_error: 0.0025
Epoch 17/50
Epoch 00016: val_loss did not improve
2s - loss: 0.0027 - acc: 0.7284 - mean_squared_error: 0.0027 - val_loss: 0.0022 - val_acc: 0.7430 - val_mean_squared_error: 0.0022
Epoch 18/50
Epoch 00017: val_loss did not improve
2s - loss: 0.0023 - acc: 0.7237 - mean_squared_error: 0.0023 - val_loss: 0.0024 - val_acc: 0.7313 - val_mean_squared_error: 0.0024
Epoch 19/50
Epoch 00018: val_loss improved from 0.00188 to 0.00152, saving model to ./model/RMSprop_model.weights.best.hdf5
2s - loss: 0.0024 - acc: 0.7447 - mean_squared_error: 0.0024 - val_loss: 0.0015 - val_acc: 0.7383 - val_mean_squared_error: 0.0015
Epoch 20/50
Epoch 00019: val_loss did not improve
2s - loss: 0.0021 - acc: 0.7523 - mean_squared_error: 0.0021 - val_loss: 0.0017 - val_acc: 0.7407 - val_mean_squared_error: 0.0017
Epoch 21/50
Epoch 00020: val_loss improved from 0.00152 to 0.00151, saving model to ./model/RMSprop_model.weights.best.hdf5
2s - loss: 0.0021 - acc: 0.7494 - mean_squared_error: 0.0021 - val_loss: 0.0015 - val_acc: 0.7523 - val_mean_squared_error: 0.0015
Epoch 22/50
Epoch 00021: val_loss did not improve
2s - loss: 0.0019 - acc: 0.7494 - mean_squared_error: 0.0019 - val_loss: 0.0016 - val_acc: 0.7617 - val_mean_squared_error: 0.0016
Epoch 23/50
Epoch 00022: val_loss improved from 0.00151 to 0.00139, saving model to ./model/RMSprop_model.weights.best.hdf5
2s - loss: 0.0019 - acc: 0.7687 - mean_squared_error: 0.0019 - val_loss: 0.0014 - val_acc: 0.7640 - val_mean_squared_error: 0.0014
Epoch 24/50
Epoch 00023: val_loss did not improve
2s - loss: 0.0018 - acc: 0.7605 - mean_squared_error: 0.0018 - val_loss: 0.0015 - val_acc: 0.7593 - val_mean_squared_error: 0.0015
Epoch 25/50
Epoch 00024: val_loss did not improve
2s - loss: 0.0017 - acc: 0.7646 - mean_squared_error: 0.0017 - val_loss: 0.0019 - val_acc: 0.7290 - val_mean_squared_error: 0.0019
Epoch 26/50
Epoch 00025: val_loss improved from 0.00139 to 0.00134, saving model to ./model/RMSprop_model.weights.best.hdf5
2s - loss: 0.0017 - acc: 0.7798 - mean_squared_error: 0.0017 - val_loss: 0.0013 - val_acc: 0.7523 - val_mean_squared_error: 0.0013
Epoch 27/50
Epoch 00026: val_loss did not improve
2s - loss: 0.0017 - acc: 0.7827 - mean_squared_error: 0.0017 - val_loss: 0.0016 - val_acc: 0.7780 - val_mean_squared_error: 0.0016
Epoch 28/50
Epoch 00027: val_loss improved from 0.00134 to 0.00129, saving model to ./model/RMSprop_model.weights.best.hdf5
2s - loss: 0.0016 - acc: 0.7646 - mean_squared_error: 0.0016 - val_loss: 0.0013 - val_acc: 0.7570 - val_mean_squared_error: 0.0013
Epoch 29/50
Epoch 00028: val_loss improved from 0.00129 to 0.00125, saving model to ./model/RMSprop_model.weights.best.hdf5
2s - loss: 0.0015 - acc: 0.7763 - mean_squared_error: 0.0015 - val_loss: 0.0012 - val_acc: 0.7664 - val_mean_squared_error: 0.0012
Epoch 30/50
Epoch 00029: val_loss did not improve
2s - loss: 0.0015 - acc: 0.7926 - mean_squared_error: 0.0015 - val_loss: 0.0013 - val_acc: 0.7687 - val_mean_squared_error: 0.0013
Epoch 31/50
Epoch 00030: val_loss did not improve
2s - loss: 0.0015 - acc: 0.7862 - mean_squared_error: 0.0015 - val_loss: 0.0013 - val_acc: 0.7710 - val_mean_squared_error: 0.0013
Epoch 32/50
Epoch 00031: val_loss improved from 0.00125 to 0.00115, saving model to ./model/RMSprop_model.weights.best.hdf5
2s - loss: 0.0014 - acc: 0.7915 - mean_squared_error: 0.0014 - val_loss: 0.0012 - val_acc: 0.7734 - val_mean_squared_error: 0.0012
Epoch 33/50
Epoch 00032: val_loss did not improve
2s - loss: 0.0014 - acc: 0.7880 - mean_squared_error: 0.0014 - val_loss: 0.0012 - val_acc: 0.7523 - val_mean_squared_error: 0.0012
Epoch 34/50
Epoch 00033: val_loss did not improve
2s - loss: 0.0014 - acc: 0.8061 - mean_squared_error: 0.0014 - val_loss: 0.0012 - val_acc: 0.7921 - val_mean_squared_error: 0.0012
Epoch 35/50
Epoch 00034: val_loss did not improve
2s - loss: 0.0013 - acc: 0.7967 - mean_squared_error: 0.0013 - val_loss: 0.0014 - val_acc: 0.7664 - val_mean_squared_error: 0.0014
Epoch 36/50
Epoch 00035: val_loss did not improve
2s - loss: 0.0013 - acc: 0.7862 - mean_squared_error: 0.0013 - val_loss: 0.0014 - val_acc: 0.7547 - val_mean_squared_error: 0.0014
Epoch 37/50
Epoch 00036: val_loss did not improve
2s - loss: 0.0013 - acc: 0.8143 - mean_squared_error: 0.0013 - val_loss: 0.0012 - val_acc: 0.7850 - val_mean_squared_error: 0.0012
Epoch 38/50
Epoch 00037: val_loss did not improve
2s - loss: 0.0012 - acc: 0.8154 - mean_squared_error: 0.0012 - val_loss: 0.0012 - val_acc: 0.7874 - val_mean_squared_error: 0.0012
Epoch 39/50
Epoch 00038: val_loss did not improve
2s - loss: 0.0012 - acc: 0.8107 - mean_squared_error: 0.0012 - val_loss: 0.0013 - val_acc: 0.7757 - val_mean_squared_error: 0.0013
Epoch 40/50
Epoch 00039: val_loss did not improve
2s - loss: 0.0011 - acc: 0.8090 - mean_squared_error: 0.0011 - val_loss: 0.0013 - val_acc: 0.7710 - val_mean_squared_error: 0.0013
Epoch 41/50
Epoch 00040: val_loss did not improve
2s - loss: 0.0011 - acc: 0.7950 - mean_squared_error: 0.0011 - val_loss: 0.0013 - val_acc: 0.8107 - val_mean_squared_error: 0.0013
Epoch 42/50
Epoch 00041: val_loss improved from 0.00115 to 0.00110, saving model to ./model/RMSprop_model.weights.best.hdf5
2s - loss: 0.0011 - acc: 0.8248 - mean_squared_error: 0.0011 - val_loss: 0.0011 - val_acc: 0.8084 - val_mean_squared_error: 0.0011
Epoch 43/50
Epoch 00042: val_loss improved from 0.00110 to 0.00108, saving model to ./model/RMSprop_model.weights.best.hdf5
2s - loss: 0.0011 - acc: 0.8201 - mean_squared_error: 0.0011 - val_loss: 0.0011 - val_acc: 0.8131 - val_mean_squared_error: 0.0011
Epoch 44/50
Epoch 00043: val_loss did not improve
2s - loss: 0.0011 - acc: 0.8096 - mean_squared_error: 0.0011 - val_loss: 0.0011 - val_acc: 0.8037 - val_mean_squared_error: 0.0011
Epoch 45/50
Epoch 00044: val_loss improved from 0.00108 to 0.00106, saving model to ./model/RMSprop_model.weights.best.hdf5
2s - loss: 0.0010 - acc: 0.8213 - mean_squared_error: 0.0010 - val_loss: 0.0011 - val_acc: 0.7944 - val_mean_squared_error: 0.0011
Epoch 46/50
Epoch 00045: val_loss did not improve
2s - loss: 9.9709e-04 - acc: 0.8166 - mean_squared_error: 9.9709e-04 - val_loss: 0.0015 - val_acc: 0.8224 - val_mean_squared_error: 0.0015
Epoch 47/50
Epoch 00046: val_loss did not improve
2s - loss: 0.0010 - acc: 0.8148 - mean_squared_error: 0.0010 - val_loss: 0.0011 - val_acc: 0.7944 - val_mean_squared_error: 0.0011
Epoch 48/50
Epoch 00047: val_loss did not improve
2s - loss: 9.9569e-04 - acc: 0.8154 - mean_squared_error: 9.9569e-04 - val_loss: 0.0011 - val_acc: 0.8084 - val_mean_squared_error: 0.0011
Epoch 49/50
Epoch 00048: val_loss did not improve
2s - loss: 9.6123e-04 - acc: 0.8084 - mean_squared_error: 9.6123e-04 - val_loss: 0.0011 - val_acc: 0.8037 - val_mean_squared_error: 0.0011
Epoch 50/50
Epoch 00049: val_loss did not improve
2s - loss: 9.3249e-04 - acc: 0.8131 - mean_squared_error: 9.3249e-04 - val_loss: 0.0012 - val_acc: 0.7640 - val_mean_squared_error: 0.0012
Running model: base_model w/opt: Adagrad
Train on 1712 samples, validate on 428 samples
Epoch 1/50
Epoch 00000: val_loss improved from inf to 0.00827, saving model to ./model/Adagrad_model.weights.best.hdf5
3s - loss: 65.7618 - acc: 0.3873 - mean_squared_error: 65.7618 - val_loss: 0.0083 - val_acc: 0.6963 - val_mean_squared_error: 0.0083
Epoch 2/50
Epoch 00001: val_loss did not improve
2s - loss: 0.0205 - acc: 0.4375 - mean_squared_error: 0.0205 - val_loss: 0.0120 - val_acc: 0.5864 - val_mean_squared_error: 0.0120
Epoch 3/50
Epoch 00002: val_loss improved from 0.00827 to 0.00454, saving model to ./model/Adagrad_model.weights.best.hdf5
2s - loss: 0.0182 - acc: 0.4749 - mean_squared_error: 0.0182 - val_loss: 0.0045 - val_acc: 0.6963 - val_mean_squared_error: 0.0045
Epoch 4/50
Epoch 00003: val_loss did not improve
2s - loss: 0.0178 - acc: 0.4352 - mean_squared_error: 0.0178 - val_loss: 0.0083 - val_acc: 0.6916 - val_mean_squared_error: 0.0083
Epoch 5/50
Epoch 00004: val_loss improved from 0.00454 to 0.00431, saving model to ./model/Adagrad_model.weights.best.hdf5
2s - loss: 0.0170 - acc: 0.4597 - mean_squared_error: 0.0170 - val_loss: 0.0043 - val_acc: 0.6939 - val_mean_squared_error: 0.0043
Epoch 6/50
Epoch 00005: val_loss did not improve
2s - loss: 0.0170 - acc: 0.4574 - mean_squared_error: 0.0170 - val_loss: 0.0052 - val_acc: 0.6963 - val_mean_squared_error: 0.0052
Epoch 7/50
Epoch 00006: val_loss did not improve
2s - loss: 0.0168 - acc: 0.4796 - mean_squared_error: 0.0168 - val_loss: 0.0045 - val_acc: 0.6963 - val_mean_squared_error: 0.0045
Epoch 8/50
Epoch 00007: val_loss did not improve
2s - loss: 0.0163 - acc: 0.4766 - mean_squared_error: 0.0163 - val_loss: 0.0050 - val_acc: 0.6963 - val_mean_squared_error: 0.0050
Epoch 9/50
Epoch 00008: val_loss improved from 0.00431 to 0.00368, saving model to ./model/Adagrad_model.weights.best.hdf5
2s - loss: 0.0160 - acc: 0.4556 - mean_squared_error: 0.0160 - val_loss: 0.0037 - val_acc: 0.7103 - val_mean_squared_error: 0.0037
Epoch 10/50
Epoch 00009: val_loss did not improve
2s - loss: 0.0157 - acc: 0.4568 - mean_squared_error: 0.0157 - val_loss: 0.0042 - val_acc: 0.6939 - val_mean_squared_error: 0.0042
Epoch 11/50
Epoch 00010: val_loss improved from 0.00368 to 0.00347, saving model to ./model/Adagrad_model.weights.best.hdf5
2s - loss: 0.0154 - acc: 0.4755 - mean_squared_error: 0.0154 - val_loss: 0.0035 - val_acc: 0.6939 - val_mean_squared_error: 0.0035
Epoch 12/50
Epoch 00011: val_loss did not improve
2s - loss: 0.0150 - acc: 0.4918 - mean_squared_error: 0.0150 - val_loss: 0.0053 - val_acc: 0.7266 - val_mean_squared_error: 0.0053
Epoch 13/50
Epoch 00012: val_loss did not improve
2s - loss: 0.0151 - acc: 0.4597 - mean_squared_error: 0.0151 - val_loss: 0.0035 - val_acc: 0.6963 - val_mean_squared_error: 0.0035
Epoch 14/50
Epoch 00013: val_loss improved from 0.00347 to 0.00290, saving model to ./model/Adagrad_model.weights.best.hdf5
2s - loss: 0.0146 - acc: 0.4965 - mean_squared_error: 0.0146 - val_loss: 0.0029 - val_acc: 0.7009 - val_mean_squared_error: 0.0029
Epoch 15/50
Epoch 00014: val_loss did not improve
2s - loss: 0.0146 - acc: 0.4766 - mean_squared_error: 0.0146 - val_loss: 0.0040 - val_acc: 0.6986 - val_mean_squared_error: 0.0040
Epoch 16/50
Epoch 00015: val_loss did not improve
2s - loss: 0.0139 - acc: 0.4825 - mean_squared_error: 0.0139 - val_loss: 0.0046 - val_acc: 0.7009 - val_mean_squared_error: 0.0046
Epoch 17/50
Epoch 00016: val_loss did not improve
2s - loss: 0.0139 - acc: 0.4807 - mean_squared_error: 0.0139 - val_loss: 0.0030 - val_acc: 0.6939 - val_mean_squared_error: 0.0030
Epoch 18/50
Epoch 00017: val_loss did not improve
2s - loss: 0.0136 - acc: 0.4737 - mean_squared_error: 0.0136 - val_loss: 0.0047 - val_acc: 0.7523 - val_mean_squared_error: 0.0047
Epoch 19/50
Epoch 00018: val_loss did not improve
2s - loss: 0.0137 - acc: 0.4813 - mean_squared_error: 0.0137 - val_loss: 0.0039 - val_acc: 0.7056 - val_mean_squared_error: 0.0039
Epoch 20/50
Epoch 00019: val_loss did not improve
2s - loss: 0.0134 - acc: 0.4877 - mean_squared_error: 0.0134 - val_loss: 0.0034 - val_acc: 0.7033 - val_mean_squared_error: 0.0034
Epoch 21/50
Epoch 00020: val_loss improved from 0.00290 to 0.00273, saving model to ./model/Adagrad_model.weights.best.hdf5
2s - loss: 0.0133 - acc: 0.4924 - mean_squared_error: 0.0133 - val_loss: 0.0027 - val_acc: 0.7103 - val_mean_squared_error: 0.0027
Epoch 22/50
Epoch 00021: val_loss did not improve
2s - loss: 0.0130 - acc: 0.4907 - mean_squared_error: 0.0130 - val_loss: 0.0041 - val_acc: 0.7150 - val_mean_squared_error: 0.0041
Epoch 23/50
Epoch 00022: val_loss improved from 0.00273 to 0.00262, saving model to ./model/Adagrad_model.weights.best.hdf5
2s - loss: 0.0131 - acc: 0.4994 - mean_squared_error: 0.0131 - val_loss: 0.0026 - val_acc: 0.7477 - val_mean_squared_error: 0.0026
Epoch 24/50
Epoch 00023: val_loss improved from 0.00262 to 0.00240, saving model to ./model/Adagrad_model.weights.best.hdf5
2s - loss: 0.0128 - acc: 0.4895 - mean_squared_error: 0.0128 - val_loss: 0.0024 - val_acc: 0.7453 - val_mean_squared_error: 0.0024
Epoch 25/50
Epoch 00024: val_loss did not improve
2s - loss: 0.0127 - acc: 0.5023 - mean_squared_error: 0.0127 - val_loss: 0.0033 - val_acc: 0.7313 - val_mean_squared_error: 0.0033
Epoch 26/50
Epoch 00025: val_loss improved from 0.00240 to 0.00223, saving model to ./model/Adagrad_model.weights.best.hdf5
2s - loss: 0.0124 - acc: 0.5053 - mean_squared_error: 0.0124 - val_loss: 0.0022 - val_acc: 0.7103 - val_mean_squared_error: 0.0022
Epoch 27/50
Epoch 00026: val_loss did not improve
2s - loss: 0.0121 - acc: 0.4912 - mean_squared_error: 0.0121 - val_loss: 0.0047 - val_acc: 0.7173 - val_mean_squared_error: 0.0047
Epoch 28/50
Epoch 00027: val_loss did not improve
2s - loss: 0.0123 - acc: 0.4994 - mean_squared_error: 0.0123 - val_loss: 0.0032 - val_acc: 0.7266 - val_mean_squared_error: 0.0032
Epoch 29/50
Epoch 00028: val_loss did not improve
2s - loss: 0.0119 - acc: 0.5169 - mean_squared_error: 0.0119 - val_loss: 0.0027 - val_acc: 0.7173 - val_mean_squared_error: 0.0027
Epoch 30/50
Epoch 00029: val_loss did not improve
2s - loss: 0.0118 - acc: 0.5035 - mean_squared_error: 0.0118 - val_loss: 0.0030 - val_acc: 0.7079 - val_mean_squared_error: 0.0030
Epoch 31/50
Epoch 00030: val_loss did not improve
2s - loss: 0.0118 - acc: 0.4942 - mean_squared_error: 0.0118 - val_loss: 0.0031 - val_acc: 0.7196 - val_mean_squared_error: 0.0031
Epoch 32/50
Epoch 00031: val_loss did not improve
2s - loss: 0.0118 - acc: 0.4988 - mean_squared_error: 0.0118 - val_loss: 0.0041 - val_acc: 0.7196 - val_mean_squared_error: 0.0041
Epoch 33/50
Epoch 00032: val_loss did not improve
2s - loss: 0.0117 - acc: 0.5134 - mean_squared_error: 0.0117 - val_loss: 0.0024 - val_acc: 0.7150 - val_mean_squared_error: 0.0024
Epoch 34/50
Epoch 00033: val_loss did not improve
2s - loss: 0.0115 - acc: 0.5053 - mean_squared_error: 0.0115 - val_loss: 0.0030 - val_acc: 0.7196 - val_mean_squared_error: 0.0030
Epoch 35/50
Epoch 00034: val_loss did not improve
2s - loss: 0.0113 - acc: 0.5012 - mean_squared_error: 0.0113 - val_loss: 0.0028 - val_acc: 0.7453 - val_mean_squared_error: 0.0028
Epoch 36/50
Epoch 00035: val_loss did not improve
2s - loss: 0.0113 - acc: 0.5199 - mean_squared_error: 0.0113 - val_loss: 0.0034 - val_acc: 0.7150 - val_mean_squared_error: 0.0034
Epoch 37/50
Epoch 00036: val_loss did not improve
2s - loss: 0.0113 - acc: 0.5280 - mean_squared_error: 0.0113 - val_loss: 0.0028 - val_acc: 0.7290 - val_mean_squared_error: 0.0028
Epoch 38/50
Epoch 00037: val_loss improved from 0.00223 to 0.00208, saving model to ./model/Adagrad_model.weights.best.hdf5
2s - loss: 0.0115 - acc: 0.5088 - mean_squared_error: 0.0115 - val_loss: 0.0021 - val_acc: 0.7360 - val_mean_squared_error: 0.0021
Epoch 39/50
Epoch 00038: val_loss did not improve
2s - loss: 0.0110 - acc: 0.5199 - mean_squared_error: 0.0110 - val_loss: 0.0034 - val_acc: 0.7523 - val_mean_squared_error: 0.0034
Epoch 40/50
Epoch 00039: val_loss did not improve
2s - loss: 0.0112 - acc: 0.5239 - mean_squared_error: 0.0112 - val_loss: 0.0025 - val_acc: 0.7079 - val_mean_squared_error: 0.0025
Epoch 41/50
Epoch 00040: val_loss improved from 0.00208 to 0.00191, saving model to ./model/Adagrad_model.weights.best.hdf5
2s - loss: 0.0109 - acc: 0.5327 - mean_squared_error: 0.0109 - val_loss: 0.0019 - val_acc: 0.7336 - val_mean_squared_error: 0.0019
Epoch 42/50
Epoch 00041: val_loss did not improve
2s - loss: 0.0109 - acc: 0.5292 - mean_squared_error: 0.0109 - val_loss: 0.0022 - val_acc: 0.7500 - val_mean_squared_error: 0.0022
Epoch 43/50
Epoch 00042: val_loss did not improve
2s - loss: 0.0104 - acc: 0.5280 - mean_squared_error: 0.0104 - val_loss: 0.0025 - val_acc: 0.7453 - val_mean_squared_error: 0.0025
Epoch 44/50
Epoch 00043: val_loss did not improve
2s - loss: 0.0106 - acc: 0.5590 - mean_squared_error: 0.0106 - val_loss: 0.0039 - val_acc: 0.7523 - val_mean_squared_error: 0.0039
Epoch 45/50
Epoch 00044: val_loss did not improve
2s - loss: 0.0104 - acc: 0.5082 - mean_squared_error: 0.0104 - val_loss: 0.0028 - val_acc: 0.7243 - val_mean_squared_error: 0.0028
Epoch 46/50
Epoch 00045: val_loss did not improve
2s - loss: 0.0105 - acc: 0.5380 - mean_squared_error: 0.0105 - val_loss: 0.0025 - val_acc: 0.7383 - val_mean_squared_error: 0.0025
Epoch 47/50
Epoch 00046: val_loss did not improve
2s - loss: 0.0106 - acc: 0.5345 - mean_squared_error: 0.0106 - val_loss: 0.0022 - val_acc: 0.7290 - val_mean_squared_error: 0.0022
Epoch 48/50
Epoch 00047: val_loss did not improve
2s - loss: 0.0104 - acc: 0.5602 - mean_squared_error: 0.0104 - val_loss: 0.0024 - val_acc: 0.7266 - val_mean_squared_error: 0.0024
Epoch 49/50
Epoch 00048: val_loss did not improve
2s - loss: 0.0104 - acc: 0.5333 - mean_squared_error: 0.0104 - val_loss: 0.0023 - val_acc: 0.7360 - val_mean_squared_error: 0.0023
Epoch 50/50
Epoch 00049: val_loss did not improve
2s - loss: 0.0100 - acc: 0.5532 - mean_squared_error: 0.0100 - val_loss: 0.0019 - val_acc: 0.7500 - val_mean_squared_error: 0.0019
Running model: base_model w/opt: Adadelta
Train on 1712 samples, validate on 428 samples
Epoch 1/50
Epoch 00000: val_loss improved from inf to 0.00756, saving model to ./model/Adadelta_model.weights.best.hdf5
4s - loss: 0.0286 - acc: 0.4106 - mean_squared_error: 0.0286 - val_loss: 0.0076 - val_acc: 0.6963 - val_mean_squared_error: 0.0076
Epoch 2/50
Epoch 00001: val_loss improved from 0.00756 to 0.00507, saving model to ./model/Adadelta_model.weights.best.hdf5
3s - loss: 0.0145 - acc: 0.4988 - mean_squared_error: 0.0145 - val_loss: 0.0051 - val_acc: 0.6963 - val_mean_squared_error: 0.0051
Epoch 3/50
Epoch 00002: val_loss improved from 0.00507 to 0.00503, saving model to ./model/Adadelta_model.weights.best.hdf5
3s - loss: 0.0112 - acc: 0.5315 - mean_squared_error: 0.0112 - val_loss: 0.0050 - val_acc: 0.6963 - val_mean_squared_error: 0.0050
Epoch 4/50
Epoch 00003: val_loss improved from 0.00503 to 0.00432, saving model to ./model/Adadelta_model.weights.best.hdf5
3s - loss: 0.0092 - acc: 0.5514 - mean_squared_error: 0.0092 - val_loss: 0.0043 - val_acc: 0.6963 - val_mean_squared_error: 0.0043
Epoch 5/50
Epoch 00004: val_loss improved from 0.00432 to 0.00427, saving model to ./model/Adadelta_model.weights.best.hdf5
3s - loss: 0.0084 - acc: 0.5882 - mean_squared_error: 0.0084 - val_loss: 0.0043 - val_acc: 0.6963 - val_mean_squared_error: 0.0043
Epoch 6/50
Epoch 00005: val_loss improved from 0.00427 to 0.00420, saving model to ./model/Adadelta_model.weights.best.hdf5
3s - loss: 0.0076 - acc: 0.6104 - mean_squared_error: 0.0076 - val_loss: 0.0042 - val_acc: 0.6963 - val_mean_squared_error: 0.0042
Epoch 7/50
Epoch 00006: val_loss improved from 0.00420 to 0.00410, saving model to ./model/Adadelta_model.weights.best.hdf5
3s - loss: 0.0070 - acc: 0.6215 - mean_squared_error: 0.0070 - val_loss: 0.0041 - val_acc: 0.6963 - val_mean_squared_error: 0.0041
Epoch 8/50
Epoch 00007: val_loss improved from 0.00410 to 0.00408, saving model to ./model/Adadelta_model.weights.best.hdf5
3s - loss: 0.0068 - acc: 0.6279 - mean_squared_error: 0.0068 - val_loss: 0.0041 - val_acc: 0.6963 - val_mean_squared_error: 0.0041
Epoch 9/50
Epoch 00008: val_loss did not improve
2s - loss: 0.0064 - acc: 0.6221 - mean_squared_error: 0.0064 - val_loss: 0.0041 - val_acc: 0.6963 - val_mean_squared_error: 0.0041
Epoch 10/50
Epoch 00009: val_loss did not improve
2s - loss: 0.0061 - acc: 0.6565 - mean_squared_error: 0.0061 - val_loss: 0.0042 - val_acc: 0.6963 - val_mean_squared_error: 0.0042
Epoch 11/50
Epoch 00010: val_loss improved from 0.00408 to 0.00375, saving model to ./model/Adadelta_model.weights.best.hdf5
3s - loss: 0.0059 - acc: 0.6659 - mean_squared_error: 0.0059 - val_loss: 0.0037 - val_acc: 0.6963 - val_mean_squared_error: 0.0037
Epoch 12/50
Epoch 00011: val_loss improved from 0.00375 to 0.00351, saving model to ./model/Adadelta_model.weights.best.hdf5
3s - loss: 0.0055 - acc: 0.6682 - mean_squared_error: 0.0055 - val_loss: 0.0035 - val_acc: 0.6963 - val_mean_squared_error: 0.0035
Epoch 13/50
Epoch 00012: val_loss did not improve
2s - loss: 0.0055 - acc: 0.6793 - mean_squared_error: 0.0055 - val_loss: 0.0045 - val_acc: 0.6963 - val_mean_squared_error: 0.0045
Epoch 14/50
Epoch 00013: val_loss improved from 0.00351 to 0.00332, saving model to ./model/Adadelta_model.weights.best.hdf5
3s - loss: 0.0053 - acc: 0.6916 - mean_squared_error: 0.0053 - val_loss: 0.0033 - val_acc: 0.6963 - val_mean_squared_error: 0.0033
Epoch 15/50
Epoch 00014: val_loss improved from 0.00332 to 0.00327, saving model to ./model/Adadelta_model.weights.best.hdf5
3s - loss: 0.0049 - acc: 0.6776 - mean_squared_error: 0.0049 - val_loss: 0.0033 - val_acc: 0.6963 - val_mean_squared_error: 0.0033
Epoch 16/50
Epoch 00015: val_loss improved from 0.00327 to 0.00313, saving model to ./model/Adadelta_model.weights.best.hdf5
3s - loss: 0.0049 - acc: 0.6811 - mean_squared_error: 0.0049 - val_loss: 0.0031 - val_acc: 0.7009 - val_mean_squared_error: 0.0031
Epoch 17/50
Epoch 00016: val_loss improved from 0.00313 to 0.00307, saving model to ./model/Adadelta_model.weights.best.hdf5
3s - loss: 0.0048 - acc: 0.6811 - mean_squared_error: 0.0048 - val_loss: 0.0031 - val_acc: 0.6963 - val_mean_squared_error: 0.0031
Epoch 18/50
Epoch 00017: val_loss improved from 0.00307 to 0.00302, saving model to ./model/Adadelta_model.weights.best.hdf5
3s - loss: 0.0046 - acc: 0.6922 - mean_squared_error: 0.0046 - val_loss: 0.0030 - val_acc: 0.6963 - val_mean_squared_error: 0.0030
Epoch 19/50
Epoch 00018: val_loss did not improve
2s - loss: 0.0044 - acc: 0.6735 - mean_squared_error: 0.0044 - val_loss: 0.0030 - val_acc: 0.6986 - val_mean_squared_error: 0.0030
Epoch 20/50
Epoch 00019: val_loss did not improve
2s - loss: 0.0044 - acc: 0.6974 - mean_squared_error: 0.0044 - val_loss: 0.0034 - val_acc: 0.7056 - val_mean_squared_error: 0.0034
Epoch 21/50
Epoch 00020: val_loss improved from 0.00302 to 0.00290, saving model to ./model/Adadelta_model.weights.best.hdf5
3s - loss: 0.0042 - acc: 0.6887 - mean_squared_error: 0.0042 - val_loss: 0.0029 - val_acc: 0.6963 - val_mean_squared_error: 0.0029
Epoch 22/50
Epoch 00021: val_loss improved from 0.00290 to 0.00286, saving model to ./model/Adadelta_model.weights.best.hdf5
3s - loss: 0.0040 - acc: 0.6875 - mean_squared_error: 0.0040 - val_loss: 0.0029 - val_acc: 0.7150 - val_mean_squared_error: 0.0029
Epoch 23/50
Epoch 00022: val_loss improved from 0.00286 to 0.00276, saving model to ./model/Adadelta_model.weights.best.hdf5
3s - loss: 0.0040 - acc: 0.6998 - mean_squared_error: 0.0040 - val_loss: 0.0028 - val_acc: 0.7150 - val_mean_squared_error: 0.0028
Epoch 24/50
Epoch 00023: val_loss improved from 0.00276 to 0.00258, saving model to ./model/Adadelta_model.weights.best.hdf5
3s - loss: 0.0039 - acc: 0.6986 - mean_squared_error: 0.0039 - val_loss: 0.0026 - val_acc: 0.7103 - val_mean_squared_error: 0.0026
Epoch 25/50
Epoch 00024: val_loss did not improve
2s - loss: 0.0038 - acc: 0.6980 - mean_squared_error: 0.0038 - val_loss: 0.0026 - val_acc: 0.7126 - val_mean_squared_error: 0.0026
Epoch 26/50
Epoch 00025: val_loss improved from 0.00258 to 0.00244, saving model to ./model/Adadelta_model.weights.best.hdf5
3s - loss: 0.0036 - acc: 0.7056 - mean_squared_error: 0.0036 - val_loss: 0.0024 - val_acc: 0.7056 - val_mean_squared_error: 0.0024
Epoch 27/50
Epoch 00026: val_loss did not improve
2s - loss: 0.0035 - acc: 0.6998 - mean_squared_error: 0.0035 - val_loss: 0.0025 - val_acc: 0.7126 - val_mean_squared_error: 0.0025
Epoch 28/50
Epoch 00027: val_loss improved from 0.00244 to 0.00238, saving model to ./model/Adadelta_model.weights.best.hdf5
3s - loss: 0.0034 - acc: 0.7062 - mean_squared_error: 0.0034 - val_loss: 0.0024 - val_acc: 0.7103 - val_mean_squared_error: 0.0024
Epoch 29/50
Epoch 00028: val_loss improved from 0.00238 to 0.00227, saving model to ./model/Adadelta_model.weights.best.hdf5
3s - loss: 0.0034 - acc: 0.6963 - mean_squared_error: 0.0034 - val_loss: 0.0023 - val_acc: 0.7173 - val_mean_squared_error: 0.0023
Epoch 30/50
Epoch 00029: val_loss did not improve
2s - loss: 0.0033 - acc: 0.6939 - mean_squared_error: 0.0033 - val_loss: 0.0023 - val_acc: 0.7196 - val_mean_squared_error: 0.0023
Epoch 31/50
Epoch 00030: val_loss did not improve
2s - loss: 0.0032 - acc: 0.7068 - mean_squared_error: 0.0032 - val_loss: 0.0024 - val_acc: 0.7173 - val_mean_squared_error: 0.0024
Epoch 32/50
Epoch 00031: val_loss improved from 0.00227 to 0.00215, saving model to ./model/Adadelta_model.weights.best.hdf5
3s - loss: 0.0032 - acc: 0.7015 - mean_squared_error: 0.0032 - val_loss: 0.0022 - val_acc: 0.7173 - val_mean_squared_error: 0.0022
Epoch 33/50
Epoch 00032: val_loss did not improve
2s - loss: 0.0031 - acc: 0.7079 - mean_squared_error: 0.0031 - val_loss: 0.0022 - val_acc: 0.7196 - val_mean_squared_error: 0.0022
Epoch 34/50
Epoch 00033: val_loss improved from 0.00215 to 0.00212, saving model to ./model/Adadelta_model.weights.best.hdf5
3s - loss: 0.0030 - acc: 0.7074 - mean_squared_error: 0.0030 - val_loss: 0.0021 - val_acc: 0.7126 - val_mean_squared_error: 0.0021
Epoch 35/50
Epoch 00034: val_loss improved from 0.00212 to 0.00207, saving model to ./model/Adadelta_model.weights.best.hdf5
3s - loss: 0.0030 - acc: 0.7138 - mean_squared_error: 0.0030 - val_loss: 0.0021 - val_acc: 0.7173 - val_mean_squared_error: 0.0021
Epoch 36/50
Epoch 00035: val_loss did not improve
2s - loss: 0.0030 - acc: 0.7120 - mean_squared_error: 0.0030 - val_loss: 0.0023 - val_acc: 0.7196 - val_mean_squared_error: 0.0023
Epoch 37/50
Epoch 00036: val_loss improved from 0.00207 to 0.00205, saving model to ./model/Adadelta_model.weights.best.hdf5
3s - loss: 0.0029 - acc: 0.7074 - mean_squared_error: 0.0029 - val_loss: 0.0020 - val_acc: 0.7103 - val_mean_squared_error: 0.0020
Epoch 38/50
Epoch 00037: val_loss improved from 0.00205 to 0.00195, saving model to ./model/Adadelta_model.weights.best.hdf5
3s - loss: 0.0028 - acc: 0.7150 - mean_squared_error: 0.0028 - val_loss: 0.0019 - val_acc: 0.7126 - val_mean_squared_error: 0.0019
Epoch 39/50
Epoch 00038: val_loss improved from 0.00195 to 0.00195, saving model to ./model/Adadelta_model.weights.best.hdf5
3s - loss: 0.0028 - acc: 0.7079 - mean_squared_error: 0.0028 - val_loss: 0.0019 - val_acc: 0.7126 - val_mean_squared_error: 0.0019
Epoch 40/50
Epoch 00039: val_loss did not improve
2s - loss: 0.0027 - acc: 0.7103 - mean_squared_error: 0.0027 - val_loss: 0.0021 - val_acc: 0.7150 - val_mean_squared_error: 0.0021
Epoch 41/50
Epoch 00040: val_loss did not improve
2s - loss: 0.0027 - acc: 0.7202 - mean_squared_error: 0.0027 - val_loss: 0.0022 - val_acc: 0.7220 - val_mean_squared_error: 0.0022
Epoch 42/50
Epoch 00041: val_loss improved from 0.00195 to 0.00191, saving model to ./model/Adadelta_model.weights.best.hdf5
3s - loss: 0.0026 - acc: 0.7097 - mean_squared_error: 0.0026 - val_loss: 0.0019 - val_acc: 0.7196 - val_mean_squared_error: 0.0019
Epoch 43/50
Epoch 00042: val_loss improved from 0.00191 to 0.00183, saving model to ./model/Adadelta_model.weights.best.hdf5
3s - loss: 0.0026 - acc: 0.7249 - mean_squared_error: 0.0026 - val_loss: 0.0018 - val_acc: 0.7220 - val_mean_squared_error: 0.0018
Epoch 44/50
Epoch 00043: val_loss did not improve
2s - loss: 0.0026 - acc: 0.7161 - mean_squared_error: 0.0026 - val_loss: 0.0018 - val_acc: 0.7150 - val_mean_squared_error: 0.0018
Epoch 45/50
Epoch 00044: val_loss improved from 0.00183 to 0.00179, saving model to ./model/Adadelta_model.weights.best.hdf5
3s - loss: 0.0025 - acc: 0.7261 - mean_squared_error: 0.0025 - val_loss: 0.0018 - val_acc: 0.7266 - val_mean_squared_error: 0.0018
Epoch 46/50
Epoch 00045: val_loss did not improve
2s - loss: 0.0025 - acc: 0.7266 - mean_squared_error: 0.0025 - val_loss: 0.0018 - val_acc: 0.7150 - val_mean_squared_error: 0.0018
Epoch 47/50
Epoch 00046: val_loss improved from 0.00179 to 0.00179, saving model to ./model/Adadelta_model.weights.best.hdf5
3s - loss: 0.0025 - acc: 0.7167 - mean_squared_error: 0.0025 - val_loss: 0.0018 - val_acc: 0.7196 - val_mean_squared_error: 0.0018
Epoch 48/50
Epoch 00047: val_loss did not improve
2s - loss: 0.0024 - acc: 0.7109 - mean_squared_error: 0.0024 - val_loss: 0.0018 - val_acc: 0.7150 - val_mean_squared_error: 0.0018
Epoch 49/50
Epoch 00048: val_loss did not improve
2s - loss: 0.0024 - acc: 0.7208 - mean_squared_error: 0.0024 - val_loss: 0.0020 - val_acc: 0.7360 - val_mean_squared_error: 0.0020
Epoch 50/50
Epoch 00049: val_loss improved from 0.00179 to 0.00175, saving model to ./model/Adadelta_model.weights.best.hdf5
3s - loss: 0.0024 - acc: 0.7336 - mean_squared_error: 0.0024 - val_loss: 0.0017 - val_acc: 0.7243 - val_mean_squared_error: 0.0017
Running model: base_model w/opt: Adam
Train on 1712 samples, validate on 428 samples
Epoch 1/50
Epoch 00000: val_loss improved from inf to 0.00514, saving model to ./model/Adam_model.weights.best.hdf5
4s - loss: 0.0308 - acc: 0.3914 - mean_squared_error: 0.0308 - val_loss: 0.0051 - val_acc: 0.6963 - val_mean_squared_error: 0.0051
Epoch 2/50
Epoch 00001: val_loss improved from 0.00514 to 0.00498, saving model to ./model/Adam_model.weights.best.hdf5
3s - loss: 0.0099 - acc: 0.5461 - mean_squared_error: 0.0099 - val_loss: 0.0050 - val_acc: 0.6963 - val_mean_squared_error: 0.0050
Epoch 3/50
Epoch 00002: val_loss improved from 0.00498 to 0.00356, saving model to ./model/Adam_model.weights.best.hdf5
3s - loss: 0.0076 - acc: 0.6016 - mean_squared_error: 0.0076 - val_loss: 0.0036 - val_acc: 0.6939 - val_mean_squared_error: 0.0036
Epoch 4/50
Epoch 00003: val_loss improved from 0.00356 to 0.00323, saving model to ./model/Adam_model.weights.best.hdf5
3s - loss: 0.0064 - acc: 0.6419 - mean_squared_error: 0.0064 - val_loss: 0.0032 - val_acc: 0.7009 - val_mean_squared_error: 0.0032
Epoch 5/50
Epoch 00004: val_loss improved from 0.00323 to 0.00282, saving model to ./model/Adam_model.weights.best.hdf5
3s - loss: 0.0058 - acc: 0.6571 - mean_squared_error: 0.0058 - val_loss: 0.0028 - val_acc: 0.7173 - val_mean_squared_error: 0.0028
Epoch 6/50
Epoch 00005: val_loss improved from 0.00282 to 0.00241, saving model to ./model/Adam_model.weights.best.hdf5
3s - loss: 0.0051 - acc: 0.6711 - mean_squared_error: 0.0051 - val_loss: 0.0024 - val_acc: 0.7150 - val_mean_squared_error: 0.0024
Epoch 7/50
Epoch 00006: val_loss did not improve
2s - loss: 0.0044 - acc: 0.6723 - mean_squared_error: 0.0044 - val_loss: 0.0033 - val_acc: 0.7360 - val_mean_squared_error: 0.0033
Epoch 8/50
Epoch 00007: val_loss improved from 0.00241 to 0.00203, saving model to ./model/Adam_model.weights.best.hdf5
3s - loss: 0.0041 - acc: 0.6776 - mean_squared_error: 0.0041 - val_loss: 0.0020 - val_acc: 0.7173 - val_mean_squared_error: 0.0020
Epoch 9/50
Epoch 00008: val_loss did not improve
2s - loss: 0.0038 - acc: 0.6945 - mean_squared_error: 0.0038 - val_loss: 0.0021 - val_acc: 0.7196 - val_mean_squared_error: 0.0021
Epoch 10/50
Epoch 00009: val_loss did not improve
2s - loss: 0.0036 - acc: 0.6974 - mean_squared_error: 0.0036 - val_loss: 0.0023 - val_acc: 0.7173 - val_mean_squared_error: 0.0023
Epoch 11/50
Epoch 00010: val_loss improved from 0.00203 to 0.00184, saving model to ./model/Adam_model.weights.best.hdf5
3s - loss: 0.0037 - acc: 0.6852 - mean_squared_error: 0.0037 - val_loss: 0.0018 - val_acc: 0.7103 - val_mean_squared_error: 0.0018
Epoch 12/50
Epoch 00011: val_loss improved from 0.00184 to 0.00172, saving model to ./model/Adam_model.weights.best.hdf5
3s - loss: 0.0033 - acc: 0.7050 - mean_squared_error: 0.0033 - val_loss: 0.0017 - val_acc: 0.7477 - val_mean_squared_error: 0.0017
Epoch 13/50
Epoch 00012: val_loss did not improve
2s - loss: 0.0031 - acc: 0.7132 - mean_squared_error: 0.0031 - val_loss: 0.0019 - val_acc: 0.7430 - val_mean_squared_error: 0.0019
Epoch 14/50
Epoch 00013: val_loss improved from 0.00172 to 0.00166, saving model to ./model/Adam_model.weights.best.hdf5
3s - loss: 0.0030 - acc: 0.7126 - mean_squared_error: 0.0030 - val_loss: 0.0017 - val_acc: 0.7453 - val_mean_squared_error: 0.0017
Epoch 15/50
Epoch 00014: val_loss did not improve
2s - loss: 0.0028 - acc: 0.7296 - mean_squared_error: 0.0028 - val_loss: 0.0022 - val_acc: 0.7407 - val_mean_squared_error: 0.0022
Epoch 16/50
Epoch 00015: val_loss did not improve
2s - loss: 0.0027 - acc: 0.7255 - mean_squared_error: 0.0027 - val_loss: 0.0018 - val_acc: 0.7079 - val_mean_squared_error: 0.0018
Epoch 17/50
Epoch 00016: val_loss did not improve
2s - loss: 0.0027 - acc: 0.7208 - mean_squared_error: 0.0027 - val_loss: 0.0018 - val_acc: 0.7523 - val_mean_squared_error: 0.0018
Epoch 18/50
Epoch 00017: val_loss improved from 0.00166 to 0.00155, saving model to ./model/Adam_model.weights.best.hdf5
3s - loss: 0.0026 - acc: 0.7190 - mean_squared_error: 0.0026 - val_loss: 0.0015 - val_acc: 0.7407 - val_mean_squared_error: 0.0015
Epoch 19/50
Epoch 00018: val_loss did not improve
2s - loss: 0.0025 - acc: 0.7354 - mean_squared_error: 0.0025 - val_loss: 0.0016 - val_acc: 0.7383 - val_mean_squared_error: 0.0016
Epoch 20/50
Epoch 00019: val_loss improved from 0.00155 to 0.00154, saving model to ./model/Adam_model.weights.best.hdf5
3s - loss: 0.0024 - acc: 0.7477 - mean_squared_error: 0.0024 - val_loss: 0.0015 - val_acc: 0.7477 - val_mean_squared_error: 0.0015
Epoch 21/50
Epoch 00020: val_loss improved from 0.00154 to 0.00147, saving model to ./model/Adam_model.weights.best.hdf5
3s - loss: 0.0024 - acc: 0.7395 - mean_squared_error: 0.0024 - val_loss: 0.0015 - val_acc: 0.7523 - val_mean_squared_error: 0.0015
Epoch 22/50
Epoch 00021: val_loss did not improve
2s - loss: 0.0023 - acc: 0.7313 - mean_squared_error: 0.0023 - val_loss: 0.0015 - val_acc: 0.7500 - val_mean_squared_error: 0.0015
Epoch 23/50
Epoch 00022: val_loss improved from 0.00147 to 0.00136, saving model to ./model/Adam_model.weights.best.hdf5
3s - loss: 0.0021 - acc: 0.7477 - mean_squared_error: 0.0021 - val_loss: 0.0014 - val_acc: 0.7617 - val_mean_squared_error: 0.0014
Epoch 24/50
Epoch 00023: val_loss did not improve
2s - loss: 0.0021 - acc: 0.7377 - mean_squared_error: 0.0021 - val_loss: 0.0016 - val_acc: 0.7687 - val_mean_squared_error: 0.0016
Epoch 25/50
Epoch 00024: val_loss did not improve
2s - loss: 0.0022 - acc: 0.7482 - mean_squared_error: 0.0022 - val_loss: 0.0017 - val_acc: 0.7477 - val_mean_squared_error: 0.0017
Epoch 26/50
Epoch 00025: val_loss did not improve
2s - loss: 0.0021 - acc: 0.7593 - mean_squared_error: 0.0021 - val_loss: 0.0016 - val_acc: 0.7477 - val_mean_squared_error: 0.0016
Epoch 27/50
Epoch 00026: val_loss did not improve
2s - loss: 0.0019 - acc: 0.7547 - mean_squared_error: 0.0019 - val_loss: 0.0015 - val_acc: 0.7593 - val_mean_squared_error: 0.0015
Epoch 28/50
Epoch 00027: val_loss did not improve
2s - loss: 0.0020 - acc: 0.7360 - mean_squared_error: 0.0020 - val_loss: 0.0015 - val_acc: 0.7640 - val_mean_squared_error: 0.0015
Epoch 29/50
Epoch 00028: val_loss improved from 0.00136 to 0.00131, saving model to ./model/Adam_model.weights.best.hdf5
3s - loss: 0.0019 - acc: 0.7523 - mean_squared_error: 0.0019 - val_loss: 0.0013 - val_acc: 0.7430 - val_mean_squared_error: 0.0013
Epoch 30/50
Epoch 00029: val_loss improved from 0.00131 to 0.00127, saving model to ./model/Adam_model.weights.best.hdf5
3s - loss: 0.0018 - acc: 0.7576 - mean_squared_error: 0.0018 - val_loss: 0.0013 - val_acc: 0.7593 - val_mean_squared_error: 0.0013
Epoch 31/50
Epoch 00030: val_loss did not improve
2s - loss: 0.0018 - acc: 0.7564 - mean_squared_error: 0.0018 - val_loss: 0.0017 - val_acc: 0.7523 - val_mean_squared_error: 0.0017
Epoch 32/50
Epoch 00031: val_loss did not improve
2s - loss: 0.0018 - acc: 0.7588 - mean_squared_error: 0.0018 - val_loss: 0.0013 - val_acc: 0.7570 - val_mean_squared_error: 0.0013
Epoch 33/50
Epoch 00032: val_loss did not improve
2s - loss: 0.0017 - acc: 0.7664 - mean_squared_error: 0.0017 - val_loss: 0.0013 - val_acc: 0.7500 - val_mean_squared_error: 0.0013
Epoch 34/50
Epoch 00033: val_loss did not improve
2s - loss: 0.0017 - acc: 0.7611 - mean_squared_error: 0.0017 - val_loss: 0.0014 - val_acc: 0.7547 - val_mean_squared_error: 0.0014
Epoch 35/50
Epoch 00034: val_loss did not improve
2s - loss: 0.0016 - acc: 0.7739 - mean_squared_error: 0.0016 - val_loss: 0.0013 - val_acc: 0.7617 - val_mean_squared_error: 0.0013
Epoch 36/50
Epoch 00035: val_loss improved from 0.00127 to 0.00125, saving model to ./model/Adam_model.weights.best.hdf5
3s - loss: 0.0016 - acc: 0.7821 - mean_squared_error: 0.0016 - val_loss: 0.0012 - val_acc: 0.7640 - val_mean_squared_error: 0.0012
Epoch 37/50
Epoch 00036: val_loss improved from 0.00125 to 0.00125, saving model to ./model/Adam_model.weights.best.hdf5
3s - loss: 0.0015 - acc: 0.7734 - mean_squared_error: 0.0015 - val_loss: 0.0012 - val_acc: 0.7664 - val_mean_squared_error: 0.0012
Epoch 38/50
Epoch 00037: val_loss did not improve
2s - loss: 0.0015 - acc: 0.7716 - mean_squared_error: 0.0015 - val_loss: 0.0013 - val_acc: 0.7640 - val_mean_squared_error: 0.0013
Epoch 39/50
Epoch 00038: val_loss improved from 0.00125 to 0.00116, saving model to ./model/Adam_model.weights.best.hdf5
3s - loss: 0.0015 - acc: 0.7640 - mean_squared_error: 0.0015 - val_loss: 0.0012 - val_acc: 0.7734 - val_mean_squared_error: 0.0012
Epoch 40/50
Epoch 00039: val_loss did not improve
2s - loss: 0.0015 - acc: 0.7763 - mean_squared_error: 0.0015 - val_loss: 0.0012 - val_acc: 0.7617 - val_mean_squared_error: 0.0012
Epoch 41/50
Epoch 00040: val_loss did not improve
2s - loss: 0.0014 - acc: 0.7792 - mean_squared_error: 0.0014 - val_loss: 0.0012 - val_acc: 0.7617 - val_mean_squared_error: 0.0012
Epoch 42/50
Epoch 00041: val_loss did not improve
2s - loss: 0.0014 - acc: 0.7839 - mean_squared_error: 0.0014 - val_loss: 0.0012 - val_acc: 0.7710 - val_mean_squared_error: 0.0012
Epoch 43/50
Epoch 00042: val_loss did not improve
2s - loss: 0.0014 - acc: 0.7728 - mean_squared_error: 0.0014 - val_loss: 0.0012 - val_acc: 0.7850 - val_mean_squared_error: 0.0012
Epoch 44/50
Epoch 00043: val_loss improved from 0.00116 to 0.00111, saving model to ./model/Adam_model.weights.best.hdf5
3s - loss: 0.0014 - acc: 0.7798 - mean_squared_error: 0.0014 - val_loss: 0.0011 - val_acc: 0.7897 - val_mean_squared_error: 0.0011
Epoch 45/50
Epoch 00044: val_loss did not improve
2s - loss: 0.0014 - acc: 0.7921 - mean_squared_error: 0.0014 - val_loss: 0.0012 - val_acc: 0.7757 - val_mean_squared_error: 0.0012
Epoch 46/50
Epoch 00045: val_loss did not improve
2s - loss: 0.0013 - acc: 0.7985 - mean_squared_error: 0.0013 - val_loss: 0.0011 - val_acc: 0.7804 - val_mean_squared_error: 0.0011
Epoch 47/50
Epoch 00046: val_loss did not improve
2s - loss: 0.0013 - acc: 0.7810 - mean_squared_error: 0.0013 - val_loss: 0.0012 - val_acc: 0.7687 - val_mean_squared_error: 0.0012
Epoch 48/50
Epoch 00047: val_loss did not improve
2s - loss: 0.0013 - acc: 0.7839 - mean_squared_error: 0.0013 - val_loss: 0.0012 - val_acc: 0.7734 - val_mean_squared_error: 0.0012
Epoch 49/50
Epoch 00048: val_loss did not improve
2s - loss: 0.0012 - acc: 0.7979 - mean_squared_error: 0.0012 - val_loss: 0.0011 - val_acc: 0.7710 - val_mean_squared_error: 0.0011
Epoch 50/50
Epoch 00049: val_loss improved from 0.00111 to 0.00110, saving model to ./model/Adam_model.weights.best.hdf5
3s - loss: 0.0012 - acc: 0.8014 - mean_squared_error: 0.0012 - val_loss: 0.0011 - val_acc: 0.7944 - val_mean_squared_error: 0.0011
Running model: base_model w/opt: Adamax
Train on 1712 samples, validate on 428 samples
Epoch 1/50
Epoch 00000: val_loss improved from inf to 0.00478, saving model to ./model/Adamax_model.weights.best.hdf5
4s - loss: 0.0280 - acc: 0.4147 - mean_squared_error: 0.0280 - val_loss: 0.0048 - val_acc: 0.6963 - val_mean_squared_error: 0.0048
Epoch 2/50
Epoch 00001: val_loss did not improve
2s - loss: 0.0106 - acc: 0.5099 - mean_squared_error: 0.0106 - val_loss: 0.0051 - val_acc: 0.6963 - val_mean_squared_error: 0.0051
Epoch 3/50
Epoch 00002: val_loss improved from 0.00478 to 0.00473, saving model to ./model/Adamax_model.weights.best.hdf5
2s - loss: 0.0091 - acc: 0.5584 - mean_squared_error: 0.0091 - val_loss: 0.0047 - val_acc: 0.6963 - val_mean_squared_error: 0.0047
Epoch 4/50
Epoch 00003: val_loss improved from 0.00473 to 0.00356, saving model to ./model/Adamax_model.weights.best.hdf5
2s - loss: 0.0081 - acc: 0.6040 - mean_squared_error: 0.0081 - val_loss: 0.0036 - val_acc: 0.7033 - val_mean_squared_error: 0.0036
Epoch 5/50
Epoch 00004: val_loss improved from 0.00356 to 0.00311, saving model to ./model/Adamax_model.weights.best.hdf5
3s - loss: 0.0071 - acc: 0.6110 - mean_squared_error: 0.0071 - val_loss: 0.0031 - val_acc: 0.7056 - val_mean_squared_error: 0.0031
Epoch 6/50
Epoch 00005: val_loss improved from 0.00311 to 0.00289, saving model to ./model/Adamax_model.weights.best.hdf5
2s - loss: 0.0065 - acc: 0.6238 - mean_squared_error: 0.0065 - val_loss: 0.0029 - val_acc: 0.7173 - val_mean_squared_error: 0.0029
Epoch 7/50
Epoch 00006: val_loss did not improve
2s - loss: 0.0061 - acc: 0.6449 - mean_squared_error: 0.0061 - val_loss: 0.0034 - val_acc: 0.7220 - val_mean_squared_error: 0.0034
Epoch 8/50
Epoch 00007: val_loss improved from 0.00289 to 0.00242, saving model to ./model/Adamax_model.weights.best.hdf5
2s - loss: 0.0057 - acc: 0.6449 - mean_squared_error: 0.0057 - val_loss: 0.0024 - val_acc: 0.7126 - val_mean_squared_error: 0.0024
Epoch 9/50
Epoch 00008: val_loss did not improve
2s - loss: 0.0055 - acc: 0.6583 - mean_squared_error: 0.0055 - val_loss: 0.0032 - val_acc: 0.7290 - val_mean_squared_error: 0.0032
Epoch 10/50
Epoch 00009: val_loss improved from 0.00242 to 0.00218, saving model to ./model/Adamax_model.weights.best.hdf5
2s - loss: 0.0051 - acc: 0.6852 - mean_squared_error: 0.0051 - val_loss: 0.0022 - val_acc: 0.7196 - val_mean_squared_error: 0.0022
Epoch 11/50
Epoch 00010: val_loss did not improve
2s - loss: 0.0047 - acc: 0.6729 - mean_squared_error: 0.0047 - val_loss: 0.0022 - val_acc: 0.7243 - val_mean_squared_error: 0.0022
Epoch 12/50
Epoch 00011: val_loss did not improve
2s - loss: 0.0046 - acc: 0.6752 - mean_squared_error: 0.0046 - val_loss: 0.0026 - val_acc: 0.7079 - val_mean_squared_error: 0.0026
Epoch 13/50
Epoch 00012: val_loss improved from 0.00218 to 0.00204, saving model to ./model/Adamax_model.weights.best.hdf5
2s - loss: 0.0044 - acc: 0.6811 - mean_squared_error: 0.0044 - val_loss: 0.0020 - val_acc: 0.7313 - val_mean_squared_error: 0.0020
Epoch 14/50
Epoch 00013: val_loss did not improve
2s - loss: 0.0043 - acc: 0.7103 - mean_squared_error: 0.0043 - val_loss: 0.0022 - val_acc: 0.7453 - val_mean_squared_error: 0.0022
Epoch 15/50
Epoch 00014: val_loss improved from 0.00204 to 0.00187, saving model to ./model/Adamax_model.weights.best.hdf5
2s - loss: 0.0039 - acc: 0.7033 - mean_squared_error: 0.0039 - val_loss: 0.0019 - val_acc: 0.7173 - val_mean_squared_error: 0.0019
Epoch 16/50
Epoch 00015: val_loss did not improve
2s - loss: 0.0040 - acc: 0.6980 - mean_squared_error: 0.0040 - val_loss: 0.0026 - val_acc: 0.7290 - val_mean_squared_error: 0.0026
Epoch 17/50
Epoch 00016: val_loss did not improve
2s - loss: 0.0038 - acc: 0.7021 - mean_squared_error: 0.0038 - val_loss: 0.0023 - val_acc: 0.7430 - val_mean_squared_error: 0.0023
Epoch 18/50
Epoch 00017: val_loss did not improve
2s - loss: 0.0037 - acc: 0.7167 - mean_squared_error: 0.0037 - val_loss: 0.0020 - val_acc: 0.7313 - val_mean_squared_error: 0.0020
Epoch 19/50
Epoch 00018: val_loss did not improve
2s - loss: 0.0035 - acc: 0.6939 - mean_squared_error: 0.0035 - val_loss: 0.0024 - val_acc: 0.7360 - val_mean_squared_error: 0.0024
Epoch 20/50
Epoch 00019: val_loss improved from 0.00187 to 0.00178, saving model to ./model/Adamax_model.weights.best.hdf5
3s - loss: 0.0035 - acc: 0.7050 - mean_squared_error: 0.0035 - val_loss: 0.0018 - val_acc: 0.7664 - val_mean_squared_error: 0.0018
Epoch 21/50
Epoch 00020: val_loss improved from 0.00178 to 0.00161, saving model to ./model/Adamax_model.weights.best.hdf5
2s - loss: 0.0033 - acc: 0.7091 - mean_squared_error: 0.0033 - val_loss: 0.0016 - val_acc: 0.7593 - val_mean_squared_error: 0.0016
Epoch 22/50
Epoch 00021: val_loss did not improve
2s - loss: 0.0033 - acc: 0.7161 - mean_squared_error: 0.0033 - val_loss: 0.0020 - val_acc: 0.7804 - val_mean_squared_error: 0.0020
Epoch 23/50
Epoch 00022: val_loss improved from 0.00161 to 0.00161, saving model to ./model/Adamax_model.weights.best.hdf5
2s - loss: 0.0032 - acc: 0.7085 - mean_squared_error: 0.0032 - val_loss: 0.0016 - val_acc: 0.7664 - val_mean_squared_error: 0.0016
Epoch 24/50
Epoch 00023: val_loss improved from 0.00161 to 0.00158, saving model to ./model/Adamax_model.weights.best.hdf5
2s - loss: 0.0030 - acc: 0.7243 - mean_squared_error: 0.0030 - val_loss: 0.0016 - val_acc: 0.7430 - val_mean_squared_error: 0.0016
Epoch 25/50
Epoch 00024: val_loss did not improve
2s - loss: 0.0031 - acc: 0.7284 - mean_squared_error: 0.0031 - val_loss: 0.0016 - val_acc: 0.7523 - val_mean_squared_error: 0.0016
Epoch 26/50
Epoch 00025: val_loss improved from 0.00158 to 0.00151, saving model to ./model/Adamax_model.weights.best.hdf5
3s - loss: 0.0030 - acc: 0.7371 - mean_squared_error: 0.0030 - val_loss: 0.0015 - val_acc: 0.7617 - val_mean_squared_error: 0.0015
Epoch 27/50
Epoch 00026: val_loss did not improve
2s - loss: 0.0029 - acc: 0.7278 - mean_squared_error: 0.0029 - val_loss: 0.0015 - val_acc: 0.7313 - val_mean_squared_error: 0.0015
Epoch 28/50
Epoch 00027: val_loss did not improve
2s - loss: 0.0028 - acc: 0.7407 - mean_squared_error: 0.0028 - val_loss: 0.0017 - val_acc: 0.7453 - val_mean_squared_error: 0.0017
Epoch 29/50
Epoch 00028: val_loss improved from 0.00151 to 0.00143, saving model to ./model/Adamax_model.weights.best.hdf5
3s - loss: 0.0027 - acc: 0.7395 - mean_squared_error: 0.0027 - val_loss: 0.0014 - val_acc: 0.7593 - val_mean_squared_error: 0.0014
Epoch 30/50
Epoch 00029: val_loss did not improve
2s - loss: 0.0025 - acc: 0.7430 - mean_squared_error: 0.0025 - val_loss: 0.0015 - val_acc: 0.7453 - val_mean_squared_error: 0.0015
Epoch 31/50
Epoch 00030: val_loss did not improve
2s - loss: 0.0026 - acc: 0.7465 - mean_squared_error: 0.0026 - val_loss: 0.0017 - val_acc: 0.7547 - val_mean_squared_error: 0.0017
Epoch 32/50
Epoch 00031: val_loss did not improve
2s - loss: 0.0025 - acc: 0.7477 - mean_squared_error: 0.0025 - val_loss: 0.0016 - val_acc: 0.7430 - val_mean_squared_error: 0.0016
Epoch 33/50
Epoch 00032: val_loss did not improve
2s - loss: 0.0024 - acc: 0.7453 - mean_squared_error: 0.0024 - val_loss: 0.0020 - val_acc: 0.7710 - val_mean_squared_error: 0.0020
Epoch 34/50
Epoch 00033: val_loss improved from 0.00143 to 0.00142, saving model to ./model/Adamax_model.weights.best.hdf5
2s - loss: 0.0024 - acc: 0.7629 - mean_squared_error: 0.0024 - val_loss: 0.0014 - val_acc: 0.7804 - val_mean_squared_error: 0.0014
Epoch 35/50
Epoch 00034: val_loss did not improve
2s - loss: 0.0023 - acc: 0.7611 - mean_squared_error: 0.0023 - val_loss: 0.0015 - val_acc: 0.7687 - val_mean_squared_error: 0.0015
Epoch 36/50
Epoch 00035: val_loss did not improve
2s - loss: 0.0022 - acc: 0.7605 - mean_squared_error: 0.0022 - val_loss: 0.0016 - val_acc: 0.7664 - val_mean_squared_error: 0.0016
Epoch 37/50
Epoch 00036: val_loss improved from 0.00142 to 0.00137, saving model to ./model/Adamax_model.weights.best.hdf5
2s - loss: 0.0021 - acc: 0.7634 - mean_squared_error: 0.0021 - val_loss: 0.0014 - val_acc: 0.7897 - val_mean_squared_error: 0.0014
Epoch 38/50
Epoch 00037: val_loss did not improve
2s - loss: 0.0021 - acc: 0.7634 - mean_squared_error: 0.0021 - val_loss: 0.0014 - val_acc: 0.7757 - val_mean_squared_error: 0.0014
Epoch 39/50
Epoch 00038: val_loss improved from 0.00137 to 0.00131, saving model to ./model/Adamax_model.weights.best.hdf5
2s - loss: 0.0021 - acc: 0.7465 - mean_squared_error: 0.0021 - val_loss: 0.0013 - val_acc: 0.7780 - val_mean_squared_error: 0.0013
Epoch 40/50
Epoch 00039: val_loss did not improve
2s - loss: 0.0020 - acc: 0.7780 - mean_squared_error: 0.0020 - val_loss: 0.0014 - val_acc: 0.7687 - val_mean_squared_error: 0.0014
Epoch 41/50
Epoch 00040: val_loss did not improve
2s - loss: 0.0020 - acc: 0.7699 - mean_squared_error: 0.0020 - val_loss: 0.0014 - val_acc: 0.7804 - val_mean_squared_error: 0.0014
Epoch 42/50
Epoch 00041: val_loss improved from 0.00131 to 0.00125, saving model to ./model/Adamax_model.weights.best.hdf5
2s - loss: 0.0019 - acc: 0.7687 - mean_squared_error: 0.0019 - val_loss: 0.0012 - val_acc: 0.7780 - val_mean_squared_error: 0.0012
Epoch 43/50
Epoch 00042: val_loss did not improve
2s - loss: 0.0018 - acc: 0.7868 - mean_squared_error: 0.0018 - val_loss: 0.0013 - val_acc: 0.7710 - val_mean_squared_error: 0.0013
Epoch 44/50
Epoch 00043: val_loss improved from 0.00125 to 0.00121, saving model to ./model/Adamax_model.weights.best.hdf5
2s - loss: 0.0018 - acc: 0.7722 - mean_squared_error: 0.0018 - val_loss: 0.0012 - val_acc: 0.7710 - val_mean_squared_error: 0.0012
Epoch 45/50
Epoch 00044: val_loss did not improve
2s - loss: 0.0018 - acc: 0.7786 - mean_squared_error: 0.0018 - val_loss: 0.0014 - val_acc: 0.7897 - val_mean_squared_error: 0.0014
Epoch 46/50
Epoch 00045: val_loss did not improve
2s - loss: 0.0017 - acc: 0.7669 - mean_squared_error: 0.0017 - val_loss: 0.0013 - val_acc: 0.7827 - val_mean_squared_error: 0.0013
Epoch 47/50
Epoch 00046: val_loss did not improve
2s - loss: 0.0017 - acc: 0.7850 - mean_squared_error: 0.0017 - val_loss: 0.0013 - val_acc: 0.7757 - val_mean_squared_error: 0.0013
Epoch 48/50
Epoch 00047: val_loss improved from 0.00121 to 0.00120, saving model to ./model/Adamax_model.weights.best.hdf5
3s - loss: 0.0016 - acc: 0.7786 - mean_squared_error: 0.0016 - val_loss: 0.0012 - val_acc: 0.7921 - val_mean_squared_error: 0.0012
Epoch 49/50
Epoch 00048: val_loss improved from 0.00120 to 0.00118, saving model to ./model/Adamax_model.weights.best.hdf5
2s - loss: 0.0016 - acc: 0.7798 - mean_squared_error: 0.0016 - val_loss: 0.0012 - val_acc: 0.7874 - val_mean_squared_error: 0.0012
Epoch 50/50
Epoch 00049: val_loss did not improve
2s - loss: 0.0016 - acc: 0.7728 - mean_squared_error: 0.0016 - val_loss: 0.0013 - val_acc: 0.7710 - val_mean_squared_error: 0.0013
Running model: base_model w/opt: Nadam
Train on 1712 samples, validate on 428 samples
Epoch 1/50
Epoch 00000: val_loss improved from inf to 0.00644, saving model to ./model/Nadam_model.weights.best.hdf5
4s - loss: 0.0556 - acc: 0.3727 - mean_squared_error: 0.0556 - val_loss: 0.0064 - val_acc: 0.6963 - val_mean_squared_error: 0.0064
Epoch 2/50
Epoch 00001: val_loss did not improve
2s - loss: 0.0119 - acc: 0.5105 - mean_squared_error: 0.0119 - val_loss: 0.0072 - val_acc: 0.6963 - val_mean_squared_error: 0.0072
Epoch 3/50
Epoch 00002: val_loss improved from 0.00644 to 0.00389, saving model to ./model/Nadam_model.weights.best.hdf5
3s - loss: 0.0094 - acc: 0.5613 - mean_squared_error: 0.0094 - val_loss: 0.0039 - val_acc: 0.6963 - val_mean_squared_error: 0.0039
Epoch 4/50
Epoch 00003: val_loss did not improve
2s - loss: 0.0080 - acc: 0.5929 - mean_squared_error: 0.0080 - val_loss: 0.0061 - val_acc: 0.6963 - val_mean_squared_error: 0.0061
Epoch 5/50
Epoch 00004: val_loss did not improve
2s - loss: 0.0070 - acc: 0.6168 - mean_squared_error: 0.0070 - val_loss: 0.0044 - val_acc: 0.6963 - val_mean_squared_error: 0.0044
Epoch 6/50
Epoch 00005: val_loss improved from 0.00389 to 0.00328, saving model to ./model/Nadam_model.weights.best.hdf5
3s - loss: 0.0062 - acc: 0.6379 - mean_squared_error: 0.0062 - val_loss: 0.0033 - val_acc: 0.6963 - val_mean_squared_error: 0.0033
Epoch 7/50
Epoch 00006: val_loss did not improve
2s - loss: 0.0060 - acc: 0.6501 - mean_squared_error: 0.0060 - val_loss: 0.0036 - val_acc: 0.6963 - val_mean_squared_error: 0.0036
Epoch 8/50
Epoch 00007: val_loss improved from 0.00328 to 0.00301, saving model to ./model/Nadam_model.weights.best.hdf5
3s - loss: 0.0051 - acc: 0.6735 - mean_squared_error: 0.0051 - val_loss: 0.0030 - val_acc: 0.7033 - val_mean_squared_error: 0.0030
Epoch 9/50
Epoch 00008: val_loss did not improve
2s - loss: 0.0046 - acc: 0.6676 - mean_squared_error: 0.0046 - val_loss: 0.0032 - val_acc: 0.7056 - val_mean_squared_error: 0.0032
Epoch 10/50
Epoch 00009: val_loss improved from 0.00301 to 0.00225, saving model to ./model/Nadam_model.weights.best.hdf5
3s - loss: 0.0042 - acc: 0.6776 - mean_squared_error: 0.0042 - val_loss: 0.0023 - val_acc: 0.7500 - val_mean_squared_error: 0.0023
Epoch 11/50
Epoch 00010: val_loss improved from 0.00225 to 0.00193, saving model to ./model/Nadam_model.weights.best.hdf5
3s - loss: 0.0039 - acc: 0.6963 - mean_squared_error: 0.0039 - val_loss: 0.0019 - val_acc: 0.7593 - val_mean_squared_error: 0.0019
Epoch 12/50
Epoch 00011: val_loss did not improve
2s - loss: 0.0036 - acc: 0.6881 - mean_squared_error: 0.0036 - val_loss: 0.0021 - val_acc: 0.7079 - val_mean_squared_error: 0.0021
Epoch 13/50
Epoch 00012: val_loss improved from 0.00193 to 0.00177, saving model to ./model/Nadam_model.weights.best.hdf5
3s - loss: 0.0033 - acc: 0.7161 - mean_squared_error: 0.0033 - val_loss: 0.0018 - val_acc: 0.7547 - val_mean_squared_error: 0.0018
Epoch 14/50
Epoch 00013: val_loss did not improve
2s - loss: 0.0030 - acc: 0.7161 - mean_squared_error: 0.0030 - val_loss: 0.0020 - val_acc: 0.7290 - val_mean_squared_error: 0.0020
Epoch 15/50
Epoch 00014: val_loss did not improve
2s - loss: 0.0029 - acc: 0.7074 - mean_squared_error: 0.0029 - val_loss: 0.0018 - val_acc: 0.7523 - val_mean_squared_error: 0.0018
Epoch 16/50
Epoch 00015: val_loss improved from 0.00177 to 0.00156, saving model to ./model/Nadam_model.weights.best.hdf5
3s - loss: 0.0028 - acc: 0.7173 - mean_squared_error: 0.0028 - val_loss: 0.0016 - val_acc: 0.7640 - val_mean_squared_error: 0.0016
Epoch 17/50
Epoch 00016: val_loss did not improve
2s - loss: 0.0026 - acc: 0.7272 - mean_squared_error: 0.0026 - val_loss: 0.0019 - val_acc: 0.7290 - val_mean_squared_error: 0.0019
Epoch 18/50
Epoch 00017: val_loss improved from 0.00156 to 0.00156, saving model to ./model/Nadam_model.weights.best.hdf5
3s - loss: 0.0024 - acc: 0.7354 - mean_squared_error: 0.0024 - val_loss: 0.0016 - val_acc: 0.7734 - val_mean_squared_error: 0.0016
Epoch 19/50
Epoch 00018: val_loss did not improve
2s - loss: 0.0023 - acc: 0.7307 - mean_squared_error: 0.0023 - val_loss: 0.0019 - val_acc: 0.7804 - val_mean_squared_error: 0.0019
Epoch 20/50
Epoch 00019: val_loss improved from 0.00156 to 0.00152, saving model to ./model/Nadam_model.weights.best.hdf5
3s - loss: 0.0023 - acc: 0.7377 - mean_squared_error: 0.0023 - val_loss: 0.0015 - val_acc: 0.7593 - val_mean_squared_error: 0.0015
Epoch 21/50
Epoch 00020: val_loss did not improve
2s - loss: 0.0022 - acc: 0.7366 - mean_squared_error: 0.0022 - val_loss: 0.0017 - val_acc: 0.7360 - val_mean_squared_error: 0.0017
Epoch 22/50
Epoch 00021: val_loss did not improve
2s - loss: 0.0021 - acc: 0.7401 - mean_squared_error: 0.0021 - val_loss: 0.0018 - val_acc: 0.7687 - val_mean_squared_error: 0.0018
Epoch 23/50
Epoch 00022: val_loss improved from 0.00152 to 0.00141, saving model to ./model/Nadam_model.weights.best.hdf5
3s - loss: 0.0020 - acc: 0.7482 - mean_squared_error: 0.0020 - val_loss: 0.0014 - val_acc: 0.7664 - val_mean_squared_error: 0.0014
Epoch 24/50
Epoch 00023: val_loss did not improve
2s - loss: 0.0019 - acc: 0.7482 - mean_squared_error: 0.0019 - val_loss: 0.0015 - val_acc: 0.7430 - val_mean_squared_error: 0.0015
Epoch 25/50
Epoch 00024: val_loss did not improve
2s - loss: 0.0019 - acc: 0.7564 - mean_squared_error: 0.0019 - val_loss: 0.0015 - val_acc: 0.7710 - val_mean_squared_error: 0.0015
Epoch 26/50
Epoch 00025: val_loss did not improve
2s - loss: 0.0018 - acc: 0.7629 - mean_squared_error: 0.0018 - val_loss: 0.0015 - val_acc: 0.7570 - val_mean_squared_error: 0.0015
Epoch 27/50
Epoch 00026: val_loss improved from 0.00141 to 0.00123, saving model to ./model/Nadam_model.weights.best.hdf5
3s - loss: 0.0018 - acc: 0.7675 - mean_squared_error: 0.0018 - val_loss: 0.0012 - val_acc: 0.7850 - val_mean_squared_error: 0.0012
Epoch 28/50
Epoch 00027: val_loss did not improve
2s - loss: 0.0017 - acc: 0.7629 - mean_squared_error: 0.0017 - val_loss: 0.0014 - val_acc: 0.7921 - val_mean_squared_error: 0.0014
Epoch 29/50
Epoch 00028: val_loss did not improve
2s - loss: 0.0016 - acc: 0.7488 - mean_squared_error: 0.0016 - val_loss: 0.0013 - val_acc: 0.8061 - val_mean_squared_error: 0.0013
Epoch 30/50
Epoch 00029: val_loss did not improve
2s - loss: 0.0016 - acc: 0.7850 - mean_squared_error: 0.0016 - val_loss: 0.0013 - val_acc: 0.7874 - val_mean_squared_error: 0.0013
Epoch 31/50
Epoch 00030: val_loss did not improve
2s - loss: 0.0015 - acc: 0.7769 - mean_squared_error: 0.0015 - val_loss: 0.0013 - val_acc: 0.7827 - val_mean_squared_error: 0.0013
Epoch 32/50
Epoch 00031: val_loss did not improve
2s - loss: 0.0015 - acc: 0.7757 - mean_squared_error: 0.0015 - val_loss: 0.0017 - val_acc: 0.7897 - val_mean_squared_error: 0.0017
Epoch 33/50
Epoch 00032: val_loss did not improve
2s - loss: 0.0015 - acc: 0.7780 - mean_squared_error: 0.0015 - val_loss: 0.0014 - val_acc: 0.7757 - val_mean_squared_error: 0.0014
Epoch 34/50
Epoch 00033: val_loss improved from 0.00123 to 0.00122, saving model to ./model/Nadam_model.weights.best.hdf5
3s - loss: 0.0014 - acc: 0.7827 - mean_squared_error: 0.0014 - val_loss: 0.0012 - val_acc: 0.8061 - val_mean_squared_error: 0.0012
Epoch 35/50
Epoch 00034: val_loss did not improve
2s - loss: 0.0014 - acc: 0.7792 - mean_squared_error: 0.0014 - val_loss: 0.0013 - val_acc: 0.8014 - val_mean_squared_error: 0.0013
Epoch 36/50
Epoch 00035: val_loss did not improve
2s - loss: 0.0014 - acc: 0.7868 - mean_squared_error: 0.0014 - val_loss: 0.0013 - val_acc: 0.7687 - val_mean_squared_error: 0.0013
Epoch 37/50
Epoch 00036: val_loss improved from 0.00122 to 0.00114, saving model to ./model/Nadam_model.weights.best.hdf5
3s - loss: 0.0013 - acc: 0.7886 - mean_squared_error: 0.0013 - val_loss: 0.0011 - val_acc: 0.8014 - val_mean_squared_error: 0.0011
Epoch 38/50
Epoch 00037: val_loss did not improve
2s - loss: 0.0013 - acc: 0.7979 - mean_squared_error: 0.0013 - val_loss: 0.0012 - val_acc: 0.7967 - val_mean_squared_error: 0.0012
Epoch 39/50
Epoch 00038: val_loss did not improve
2s - loss: 0.0012 - acc: 0.7973 - mean_squared_error: 0.0012 - val_loss: 0.0014 - val_acc: 0.7944 - val_mean_squared_error: 0.0014
Epoch 40/50
Epoch 00039: val_loss did not improve
2s - loss: 0.0012 - acc: 0.8049 - mean_squared_error: 0.0012 - val_loss: 0.0012 - val_acc: 0.7897 - val_mean_squared_error: 0.0012
Epoch 41/50
Epoch 00040: val_loss did not improve
2s - loss: 0.0012 - acc: 0.8014 - mean_squared_error: 0.0012 - val_loss: 0.0013 - val_acc: 0.7921 - val_mean_squared_error: 0.0013
Epoch 42/50
Epoch 00041: val_loss improved from 0.00114 to 0.00112, saving model to ./model/Nadam_model.weights.best.hdf5
3s - loss: 0.0012 - acc: 0.8067 - mean_squared_error: 0.0012 - val_loss: 0.0011 - val_acc: 0.7897 - val_mean_squared_error: 0.0011
Epoch 43/50
Epoch 00042: val_loss did not improve
2s - loss: 0.0011 - acc: 0.8084 - mean_squared_error: 0.0011 - val_loss: 0.0011 - val_acc: 0.8061 - val_mean_squared_error: 0.0011
Epoch 44/50
Epoch 00043: val_loss did not improve
2s - loss: 0.0011 - acc: 0.8148 - mean_squared_error: 0.0011 - val_loss: 0.0012 - val_acc: 0.7991 - val_mean_squared_error: 0.0012
Epoch 45/50
Epoch 00044: val_loss did not improve
2s - loss: 0.0011 - acc: 0.8107 - mean_squared_error: 0.0011 - val_loss: 0.0011 - val_acc: 0.8061 - val_mean_squared_error: 0.0011
Epoch 46/50
Epoch 00045: val_loss improved from 0.00112 to 0.00108, saving model to ./model/Nadam_model.weights.best.hdf5
3s - loss: 0.0011 - acc: 0.8102 - mean_squared_error: 0.0011 - val_loss: 0.0011 - val_acc: 0.8014 - val_mean_squared_error: 0.0011
Epoch 47/50
Epoch 00046: val_loss did not improve
2s - loss: 0.0011 - acc: 0.8078 - mean_squared_error: 0.0011 - val_loss: 0.0011 - val_acc: 0.7967 - val_mean_squared_error: 0.0011
Epoch 48/50
Epoch 00047: val_loss improved from 0.00108 to 0.00108, saving model to ./model/Nadam_model.weights.best.hdf5
3s - loss: 0.0011 - acc: 0.8131 - mean_squared_error: 0.0011 - val_loss: 0.0011 - val_acc: 0.7991 - val_mean_squared_error: 0.0011
Epoch 49/50
Epoch 00048: val_loss did not improve
2s - loss: 0.0010 - acc: 0.8189 - mean_squared_error: 0.0010 - val_loss: 0.0012 - val_acc: 0.8107 - val_mean_squared_error: 0.0012
Epoch 50/50
Epoch 00049: val_loss improved from 0.00108 to 0.00107, saving model to ./model/Nadam_model.weights.best.hdf5
3s - loss: 9.9799e-04 - acc: 0.8096 - mean_squared_error: 9.9799e-04 - val_loss: 0.0011 - val_acc: 0.8084 - val_mean_squared_error: 0.0011
Running model: bigger_base_model w/opt: SGD
Train on 1712 samples, validate on 428 samples
Epoch 1/50
Epoch 00000: val_loss improved from inf to 0.01324, saving model to ./model/SGD_model.weights.best.hdf5
3s - loss: 0.0673 - acc: 0.2623 - mean_squared_error: 0.0673 - val_loss: 0.0132 - val_acc: 0.6963 - val_mean_squared_error: 0.0132
Epoch 2/50
Epoch 00001: val_loss improved from 0.01324 to 0.01158, saving model to ./model/SGD_model.weights.best.hdf5
2s - loss: 0.0312 - acc: 0.3908 - mean_squared_error: 0.0312 - val_loss: 0.0116 - val_acc: 0.6963 - val_mean_squared_error: 0.0116
Epoch 3/50
Epoch 00002: val_loss improved from 0.01158 to 0.00999, saving model to ./model/SGD_model.weights.best.hdf5
2s - loss: 0.0274 - acc: 0.4095 - mean_squared_error: 0.0274 - val_loss: 0.0100 - val_acc: 0.6963 - val_mean_squared_error: 0.0100
Epoch 4/50
Epoch 00003: val_loss improved from 0.00999 to 0.00948, saving model to ./model/SGD_model.weights.best.hdf5
2s - loss: 0.0249 - acc: 0.4048 - mean_squared_error: 0.0249 - val_loss: 0.0095 - val_acc: 0.6963 - val_mean_squared_error: 0.0095
Epoch 5/50
Epoch 00004: val_loss improved from 0.00948 to 0.00925, saving model to ./model/SGD_model.weights.best.hdf5
2s - loss: 0.0233 - acc: 0.4311 - mean_squared_error: 0.0233 - val_loss: 0.0093 - val_acc: 0.6963 - val_mean_squared_error: 0.0093
Epoch 6/50
Epoch 00005: val_loss improved from 0.00925 to 0.00860, saving model to ./model/SGD_model.weights.best.hdf5
2s - loss: 0.0216 - acc: 0.4433 - mean_squared_error: 0.0216 - val_loss: 0.0086 - val_acc: 0.6963 - val_mean_squared_error: 0.0086
Epoch 7/50
Epoch 00006: val_loss improved from 0.00860 to 0.00771, saving model to ./model/SGD_model.weights.best.hdf5
2s - loss: 0.0205 - acc: 0.4515 - mean_squared_error: 0.0205 - val_loss: 0.0077 - val_acc: 0.6963 - val_mean_squared_error: 0.0077
Epoch 8/50
Epoch 00007: val_loss improved from 0.00771 to 0.00760, saving model to ./model/SGD_model.weights.best.hdf5
2s - loss: 0.0195 - acc: 0.4451 - mean_squared_error: 0.0195 - val_loss: 0.0076 - val_acc: 0.6963 - val_mean_squared_error: 0.0076
Epoch 9/50
Epoch 00008: val_loss improved from 0.00760 to 0.00752, saving model to ./model/SGD_model.weights.best.hdf5
2s - loss: 0.0186 - acc: 0.4790 - mean_squared_error: 0.0186 - val_loss: 0.0075 - val_acc: 0.6963 - val_mean_squared_error: 0.0075
Epoch 10/50
Epoch 00009: val_loss improved from 0.00752 to 0.00685, saving model to ./model/SGD_model.weights.best.hdf5
2s - loss: 0.0179 - acc: 0.4737 - mean_squared_error: 0.0179 - val_loss: 0.0069 - val_acc: 0.6963 - val_mean_squared_error: 0.0069
Epoch 11/50
Epoch 00010: val_loss did not improve
2s - loss: 0.0169 - acc: 0.4626 - mean_squared_error: 0.0169 - val_loss: 0.0069 - val_acc: 0.6963 - val_mean_squared_error: 0.0069
Epoch 12/50
Epoch 00011: val_loss improved from 0.00685 to 0.00632, saving model to ./model/SGD_model.weights.best.hdf5
2s - loss: 0.0163 - acc: 0.4790 - mean_squared_error: 0.0163 - val_loss: 0.0063 - val_acc: 0.6963 - val_mean_squared_error: 0.0063
Epoch 13/50
Epoch 00012: val_loss improved from 0.00632 to 0.00623, saving model to ./model/SGD_model.weights.best.hdf5
2s - loss: 0.0159 - acc: 0.4749 - mean_squared_error: 0.0159 - val_loss: 0.0062 - val_acc: 0.6963 - val_mean_squared_error: 0.0062
Epoch 14/50
Epoch 00013: val_loss improved from 0.00623 to 0.00607, saving model to ./model/SGD_model.weights.best.hdf5
2s - loss: 0.0152 - acc: 0.4778 - mean_squared_error: 0.0152 - val_loss: 0.0061 - val_acc: 0.6963 - val_mean_squared_error: 0.0061
Epoch 15/50
Epoch 00014: val_loss improved from 0.00607 to 0.00605, saving model to ./model/SGD_model.weights.best.hdf5
2s - loss: 0.0151 - acc: 0.4755 - mean_squared_error: 0.0151 - val_loss: 0.0061 - val_acc: 0.6963 - val_mean_squared_error: 0.0061
Epoch 16/50
Epoch 00015: val_loss improved from 0.00605 to 0.00584, saving model to ./model/SGD_model.weights.best.hdf5
2s - loss: 0.0144 - acc: 0.4895 - mean_squared_error: 0.0144 - val_loss: 0.0058 - val_acc: 0.6963 - val_mean_squared_error: 0.0058
Epoch 17/50
Epoch 00016: val_loss improved from 0.00584 to 0.00548, saving model to ./model/SGD_model.weights.best.hdf5
2s - loss: 0.0141 - acc: 0.5134 - mean_squared_error: 0.0141 - val_loss: 0.0055 - val_acc: 0.6963 - val_mean_squared_error: 0.0055
Epoch 18/50
Epoch 00017: val_loss improved from 0.00548 to 0.00535, saving model to ./model/SGD_model.weights.best.hdf5
2s - loss: 0.0138 - acc: 0.4901 - mean_squared_error: 0.0138 - val_loss: 0.0054 - val_acc: 0.6963 - val_mean_squared_error: 0.0054
Epoch 19/50
Epoch 00018: val_loss improved from 0.00535 to 0.00533, saving model to ./model/SGD_model.weights.best.hdf5
2s - loss: 0.0137 - acc: 0.4988 - mean_squared_error: 0.0137 - val_loss: 0.0053 - val_acc: 0.6963 - val_mean_squared_error: 0.0053
Epoch 20/50
Epoch 00019: val_loss did not improve
2s - loss: 0.0136 - acc: 0.5018 - mean_squared_error: 0.0136 - val_loss: 0.0053 - val_acc: 0.6963 - val_mean_squared_error: 0.0053
Epoch 21/50
Epoch 00020: val_loss did not improve
2s - loss: 0.0133 - acc: 0.5123 - mean_squared_error: 0.0133 - val_loss: 0.0054 - val_acc: 0.6963 - val_mean_squared_error: 0.0054
Epoch 22/50
Epoch 00021: val_loss improved from 0.00533 to 0.00528, saving model to ./model/SGD_model.weights.best.hdf5
2s - loss: 0.0130 - acc: 0.4918 - mean_squared_error: 0.0130 - val_loss: 0.0053 - val_acc: 0.6963 - val_mean_squared_error: 0.0053
Epoch 23/50
Epoch 00022: val_loss improved from 0.00528 to 0.00516, saving model to ./model/SGD_model.weights.best.hdf5
2s - loss: 0.0129 - acc: 0.5035 - mean_squared_error: 0.0129 - val_loss: 0.0052 - val_acc: 0.6963 - val_mean_squared_error: 0.0052
Epoch 24/50
Epoch 00023: val_loss did not improve
2s - loss: 0.0126 - acc: 0.5123 - mean_squared_error: 0.0126 - val_loss: 0.0052 - val_acc: 0.6963 - val_mean_squared_error: 0.0052
Epoch 25/50
Epoch 00024: val_loss did not improve
2s - loss: 0.0125 - acc: 0.5129 - mean_squared_error: 0.0125 - val_loss: 0.0052 - val_acc: 0.6963 - val_mean_squared_error: 0.0052
Epoch 26/50
Epoch 00025: val_loss did not improve
2s - loss: 0.0123 - acc: 0.5269 - mean_squared_error: 0.0123 - val_loss: 0.0056 - val_acc: 0.6963 - val_mean_squared_error: 0.0056
Epoch 27/50
Epoch 00026: val_loss did not improve
2s - loss: 0.0123 - acc: 0.5134 - mean_squared_error: 0.0123 - val_loss: 0.0052 - val_acc: 0.6963 - val_mean_squared_error: 0.0052
Epoch 28/50
Epoch 00027: val_loss did not improve
2s - loss: 0.0120 - acc: 0.5251 - mean_squared_error: 0.0120 - val_loss: 0.0052 - val_acc: 0.6963 - val_mean_squared_error: 0.0052
Epoch 29/50
Epoch 00028: val_loss did not improve
2s - loss: 0.0120 - acc: 0.5368 - mean_squared_error: 0.0120 - val_loss: 0.0052 - val_acc: 0.6963 - val_mean_squared_error: 0.0052
Epoch 30/50
Epoch 00029: val_loss improved from 0.00516 to 0.00508, saving model to ./model/SGD_model.weights.best.hdf5
2s - loss: 0.0118 - acc: 0.5345 - mean_squared_error: 0.0118 - val_loss: 0.0051 - val_acc: 0.6963 - val_mean_squared_error: 0.0051
Epoch 31/50
Epoch 00030: val_loss did not improve
2s - loss: 0.0118 - acc: 0.5082 - mean_squared_error: 0.0118 - val_loss: 0.0052 - val_acc: 0.6963 - val_mean_squared_error: 0.0052
Epoch 32/50
Epoch 00031: val_loss improved from 0.00508 to 0.00507, saving model to ./model/SGD_model.weights.best.hdf5
2s - loss: 0.0117 - acc: 0.5169 - mean_squared_error: 0.0117 - val_loss: 0.0051 - val_acc: 0.6963 - val_mean_squared_error: 0.0051
Epoch 33/50
Epoch 00032: val_loss improved from 0.00507 to 0.00500, saving model to ./model/SGD_model.weights.best.hdf5
2s - loss: 0.0116 - acc: 0.5532 - mean_squared_error: 0.0116 - val_loss: 0.0050 - val_acc: 0.6963 - val_mean_squared_error: 0.0050
Epoch 34/50
Epoch 00033: val_loss improved from 0.00500 to 0.00484, saving model to ./model/SGD_model.weights.best.hdf5
2s - loss: 0.0115 - acc: 0.5450 - mean_squared_error: 0.0115 - val_loss: 0.0048 - val_acc: 0.6963 - val_mean_squared_error: 0.0048
Epoch 35/50
Epoch 00034: val_loss did not improve
2s - loss: 0.0114 - acc: 0.5204 - mean_squared_error: 0.0114 - val_loss: 0.0053 - val_acc: 0.6963 - val_mean_squared_error: 0.0053
Epoch 36/50
Epoch 00035: val_loss improved from 0.00484 to 0.00477, saving model to ./model/SGD_model.weights.best.hdf5
2s - loss: 0.0114 - acc: 0.5549 - mean_squared_error: 0.0114 - val_loss: 0.0048 - val_acc: 0.6963 - val_mean_squared_error: 0.0048
Epoch 37/50
Epoch 00036: val_loss did not improve
2s - loss: 0.0112 - acc: 0.5520 - mean_squared_error: 0.0112 - val_loss: 0.0048 - val_acc: 0.6963 - val_mean_squared_error: 0.0048
Epoch 38/50
Epoch 00037: val_loss did not improve
2s - loss: 0.0111 - acc: 0.5426 - mean_squared_error: 0.0111 - val_loss: 0.0048 - val_acc: 0.6963 - val_mean_squared_error: 0.0048
Epoch 39/50
Epoch 00038: val_loss did not improve
2s - loss: 0.0109 - acc: 0.5403 - mean_squared_error: 0.0109 - val_loss: 0.0052 - val_acc: 0.6963 - val_mean_squared_error: 0.0052
Epoch 40/50
Epoch 00039: val_loss did not improve
2s - loss: 0.0110 - acc: 0.5561 - mean_squared_error: 0.0110 - val_loss: 0.0049 - val_acc: 0.6963 - val_mean_squared_error: 0.0049
Epoch 41/50
Epoch 00040: val_loss did not improve
2s - loss: 0.0108 - acc: 0.5403 - mean_squared_error: 0.0108 - val_loss: 0.0049 - val_acc: 0.6963 - val_mean_squared_error: 0.0049
Epoch 42/50
Epoch 00041: val_loss did not improve
2s - loss: 0.0109 - acc: 0.5432 - mean_squared_error: 0.0109 - val_loss: 0.0050 - val_acc: 0.6963 - val_mean_squared_error: 0.0050
Epoch 43/50
Epoch 00042: val_loss did not improve
2s - loss: 0.0107 - acc: 0.5088 - mean_squared_error: 0.0107 - val_loss: 0.0049 - val_acc: 0.6963 - val_mean_squared_error: 0.0049
Epoch 44/50
Epoch 00043: val_loss did not improve
2s - loss: 0.0105 - acc: 0.5602 - mean_squared_error: 0.0105 - val_loss: 0.0053 - val_acc: 0.6963 - val_mean_squared_error: 0.0053
Epoch 45/50
Epoch 00044: val_loss improved from 0.00477 to 0.00475, saving model to ./model/SGD_model.weights.best.hdf5
2s - loss: 0.0107 - acc: 0.5380 - mean_squared_error: 0.0107 - val_loss: 0.0048 - val_acc: 0.6963 - val_mean_squared_error: 0.0048
Epoch 46/50
Epoch 00045: val_loss did not improve
2s - loss: 0.0105 - acc: 0.5724 - mean_squared_error: 0.0105 - val_loss: 0.0051 - val_acc: 0.6963 - val_mean_squared_error: 0.0051
Epoch 47/50
Epoch 00046: val_loss did not improve
2s - loss: 0.0104 - acc: 0.5561 - mean_squared_error: 0.0104 - val_loss: 0.0048 - val_acc: 0.6963 - val_mean_squared_error: 0.0048
Epoch 48/50
Epoch 00047: val_loss improved from 0.00475 to 0.00473, saving model to ./model/SGD_model.weights.best.hdf5
2s - loss: 0.0103 - acc: 0.5689 - mean_squared_error: 0.0103 - val_loss: 0.0047 - val_acc: 0.6963 - val_mean_squared_error: 0.0047
Epoch 49/50
Epoch 00048: val_loss did not improve
2s - loss: 0.0104 - acc: 0.5520 - mean_squared_error: 0.0104 - val_loss: 0.0050 - val_acc: 0.6963 - val_mean_squared_error: 0.0050
Epoch 50/50
Epoch 00049: val_loss did not improve
2s - loss: 0.0102 - acc: 0.5730 - mean_squared_error: 0.0102 - val_loss: 0.0049 - val_acc: 0.6963 - val_mean_squared_error: 0.0049
Running model: bigger_base_model w/opt: RMSprop
Train on 1712 samples, validate on 428 samples
Epoch 1/50
Epoch 00000: val_loss improved from inf to 0.00759, saving model to ./model/RMSprop_model.weights.best.hdf5
4s - loss: 0.2430 - acc: 0.3984 - mean_squared_error: 0.2430 - val_loss: 0.0076 - val_acc: 0.6963 - val_mean_squared_error: 0.0076
Epoch 2/50
Epoch 00001: val_loss did not improve
2s - loss: 0.0196 - acc: 0.4930 - mean_squared_error: 0.0196 - val_loss: 0.0104 - val_acc: 0.6963 - val_mean_squared_error: 0.0104
Epoch 3/50
Epoch 00002: val_loss improved from 0.00759 to 0.00448, saving model to ./model/RMSprop_model.weights.best.hdf5
2s - loss: 0.0128 - acc: 0.5537 - mean_squared_error: 0.0128 - val_loss: 0.0045 - val_acc: 0.6963 - val_mean_squared_error: 0.0045
Epoch 4/50
Epoch 00003: val_loss improved from 0.00448 to 0.00414, saving model to ./model/RMSprop_model.weights.best.hdf5
2s - loss: 0.0086 - acc: 0.6133 - mean_squared_error: 0.0086 - val_loss: 0.0041 - val_acc: 0.6963 - val_mean_squared_error: 0.0041
Epoch 5/50
Epoch 00004: val_loss did not improve
2s - loss: 0.0072 - acc: 0.6507 - mean_squared_error: 0.0072 - val_loss: 0.0064 - val_acc: 0.6963 - val_mean_squared_error: 0.0064
Epoch 6/50
Epoch 00005: val_loss did not improve
2s - loss: 0.0064 - acc: 0.6706 - mean_squared_error: 0.0064 - val_loss: 0.0068 - val_acc: 0.7056 - val_mean_squared_error: 0.0068
Epoch 7/50
Epoch 00006: val_loss improved from 0.00414 to 0.00382, saving model to ./model/RMSprop_model.weights.best.hdf5
2s - loss: 0.0056 - acc: 0.6793 - mean_squared_error: 0.0056 - val_loss: 0.0038 - val_acc: 0.7033 - val_mean_squared_error: 0.0038
Epoch 8/50
Epoch 00007: val_loss did not improve
2s - loss: 0.0049 - acc: 0.6922 - mean_squared_error: 0.0049 - val_loss: 0.0040 - val_acc: 0.7103 - val_mean_squared_error: 0.0040
Epoch 9/50
Epoch 00008: val_loss improved from 0.00382 to 0.00322, saving model to ./model/RMSprop_model.weights.best.hdf5
2s - loss: 0.0045 - acc: 0.6857 - mean_squared_error: 0.0045 - val_loss: 0.0032 - val_acc: 0.7009 - val_mean_squared_error: 0.0032
Epoch 10/50
Epoch 00009: val_loss improved from 0.00322 to 0.00243, saving model to ./model/RMSprop_model.weights.best.hdf5
2s - loss: 0.0043 - acc: 0.7085 - mean_squared_error: 0.0043 - val_loss: 0.0024 - val_acc: 0.7243 - val_mean_squared_error: 0.0024
Epoch 11/50
Epoch 00010: val_loss improved from 0.00243 to 0.00232, saving model to ./model/RMSprop_model.weights.best.hdf5
2s - loss: 0.0039 - acc: 0.7150 - mean_squared_error: 0.0039 - val_loss: 0.0023 - val_acc: 0.7103 - val_mean_squared_error: 0.0023
Epoch 12/50
Epoch 00011: val_loss did not improve
2s - loss: 0.0036 - acc: 0.7179 - mean_squared_error: 0.0036 - val_loss: 0.0026 - val_acc: 0.7150 - val_mean_squared_error: 0.0026
Epoch 13/50
Epoch 00012: val_loss improved from 0.00232 to 0.00197, saving model to ./model/RMSprop_model.weights.best.hdf5
2s - loss: 0.0033 - acc: 0.7155 - mean_squared_error: 0.0033 - val_loss: 0.0020 - val_acc: 0.7079 - val_mean_squared_error: 0.0020
Epoch 14/50
Epoch 00013: val_loss did not improve
2s - loss: 0.0030 - acc: 0.7167 - mean_squared_error: 0.0030 - val_loss: 0.0022 - val_acc: 0.7079 - val_mean_squared_error: 0.0022
Epoch 15/50
Epoch 00014: val_loss did not improve
2s - loss: 0.0027 - acc: 0.7202 - mean_squared_error: 0.0027 - val_loss: 0.0037 - val_acc: 0.7336 - val_mean_squared_error: 0.0037
Epoch 16/50
Epoch 00015: val_loss did not improve
2s - loss: 0.0027 - acc: 0.7249 - mean_squared_error: 0.0027 - val_loss: 0.0021 - val_acc: 0.7383 - val_mean_squared_error: 0.0021
Epoch 17/50
Epoch 00016: val_loss did not improve
2s - loss: 0.0024 - acc: 0.7290 - mean_squared_error: 0.0024 - val_loss: 0.0024 - val_acc: 0.7150 - val_mean_squared_error: 0.0024
Epoch 18/50
Epoch 00017: val_loss did not improve
2s - loss: 0.0024 - acc: 0.7407 - mean_squared_error: 0.0024 - val_loss: 0.0024 - val_acc: 0.7150 - val_mean_squared_error: 0.0024
Epoch 19/50
Epoch 00018: val_loss improved from 0.00197 to 0.00165, saving model to ./model/RMSprop_model.weights.best.hdf5
2s - loss: 0.0023 - acc: 0.7471 - mean_squared_error: 0.0023 - val_loss: 0.0017 - val_acc: 0.7336 - val_mean_squared_error: 0.0017
Epoch 20/50
Epoch 00019: val_loss did not improve
2s - loss: 0.0022 - acc: 0.7389 - mean_squared_error: 0.0022 - val_loss: 0.0017 - val_acc: 0.7336 - val_mean_squared_error: 0.0017
Epoch 21/50
Epoch 00020: val_loss improved from 0.00165 to 0.00151, saving model to ./model/RMSprop_model.weights.best.hdf5
2s - loss: 0.0021 - acc: 0.7506 - mean_squared_error: 0.0021 - val_loss: 0.0015 - val_acc: 0.7500 - val_mean_squared_error: 0.0015
Epoch 22/50
Epoch 00021: val_loss did not improve
2s - loss: 0.0021 - acc: 0.7599 - mean_squared_error: 0.0021 - val_loss: 0.0016 - val_acc: 0.7687 - val_mean_squared_error: 0.0016
Epoch 23/50
Epoch 00022: val_loss did not improve
2s - loss: 0.0020 - acc: 0.7518 - mean_squared_error: 0.0020 - val_loss: 0.0016 - val_acc: 0.7500 - val_mean_squared_error: 0.0016
Epoch 24/50
Epoch 00023: val_loss did not improve
2s - loss: 0.0019 - acc: 0.7453 - mean_squared_error: 0.0019 - val_loss: 0.0018 - val_acc: 0.7477 - val_mean_squared_error: 0.0018
Epoch 25/50
Epoch 00024: val_loss improved from 0.00151 to 0.00135, saving model to ./model/RMSprop_model.weights.best.hdf5
2s - loss: 0.0019 - acc: 0.7664 - mean_squared_error: 0.0019 - val_loss: 0.0014 - val_acc: 0.7687 - val_mean_squared_error: 0.0014
Epoch 26/50
Epoch 00025: val_loss did not improve
2s - loss: 0.0019 - acc: 0.7640 - mean_squared_error: 0.0019 - val_loss: 0.0023 - val_acc: 0.7640 - val_mean_squared_error: 0.0023
Epoch 27/50
Epoch 00026: val_loss did not improve
2s - loss: 0.0018 - acc: 0.7576 - mean_squared_error: 0.0018 - val_loss: 0.0015 - val_acc: 0.7593 - val_mean_squared_error: 0.0015
Epoch 28/50
Epoch 00027: val_loss improved from 0.00135 to 0.00133, saving model to ./model/RMSprop_model.weights.best.hdf5
2s - loss: 0.0017 - acc: 0.7669 - mean_squared_error: 0.0017 - val_loss: 0.0013 - val_acc: 0.7710 - val_mean_squared_error: 0.0013
Epoch 29/50
Epoch 00028: val_loss did not improve
2s - loss: 0.0017 - acc: 0.7693 - mean_squared_error: 0.0017 - val_loss: 0.0014 - val_acc: 0.7593 - val_mean_squared_error: 0.0014
Epoch 30/50
Epoch 00029: val_loss did not improve
2s - loss: 0.0017 - acc: 0.7728 - mean_squared_error: 0.0017 - val_loss: 0.0014 - val_acc: 0.7640 - val_mean_squared_error: 0.0014
Epoch 31/50
Epoch 00030: val_loss did not improve
2s - loss: 0.0016 - acc: 0.7693 - mean_squared_error: 0.0016 - val_loss: 0.0020 - val_acc: 0.7407 - val_mean_squared_error: 0.0020
Epoch 32/50
Epoch 00031: val_loss did not improve
2s - loss: 0.0015 - acc: 0.7722 - mean_squared_error: 0.0015 - val_loss: 0.0014 - val_acc: 0.7710 - val_mean_squared_error: 0.0014
Epoch 33/50
Epoch 00032: val_loss did not improve
2s - loss: 0.0015 - acc: 0.7810 - mean_squared_error: 0.0015 - val_loss: 0.0014 - val_acc: 0.7827 - val_mean_squared_error: 0.0014
Epoch 34/50
Epoch 00033: val_loss did not improve
2s - loss: 0.0015 - acc: 0.7815 - mean_squared_error: 0.0015 - val_loss: 0.0015 - val_acc: 0.8037 - val_mean_squared_error: 0.0015
Epoch 35/50
Epoch 00034: val_loss did not improve
2s - loss: 0.0014 - acc: 0.7862 - mean_squared_error: 0.0014 - val_loss: 0.0013 - val_acc: 0.7944 - val_mean_squared_error: 0.0013
Epoch 36/50
Epoch 00035: val_loss did not improve
2s - loss: 0.0014 - acc: 0.7921 - mean_squared_error: 0.0014 - val_loss: 0.0015 - val_acc: 0.7757 - val_mean_squared_error: 0.0015
Epoch 37/50
Epoch 00036: val_loss did not improve
2s - loss: 0.0014 - acc: 0.7810 - mean_squared_error: 0.0014 - val_loss: 0.0018 - val_acc: 0.7967 - val_mean_squared_error: 0.0018
Epoch 38/50
Epoch 00037: val_loss improved from 0.00133 to 0.00130, saving model to ./model/RMSprop_model.weights.best.hdf5
2s - loss: 0.0013 - acc: 0.7891 - mean_squared_error: 0.0013 - val_loss: 0.0013 - val_acc: 0.7804 - val_mean_squared_error: 0.0013
Epoch 39/50
Epoch 00038: val_loss did not improve
2s - loss: 0.0013 - acc: 0.7909 - mean_squared_error: 0.0013 - val_loss: 0.0014 - val_acc: 0.7687 - val_mean_squared_error: 0.0014
Epoch 40/50
Epoch 00039: val_loss improved from 0.00130 to 0.00123, saving model to ./model/RMSprop_model.weights.best.hdf5
2s - loss: 0.0013 - acc: 0.7950 - mean_squared_error: 0.0013 - val_loss: 0.0012 - val_acc: 0.7827 - val_mean_squared_error: 0.0012
Epoch 41/50
Epoch 00040: val_loss did not improve
2s - loss: 0.0012 - acc: 0.8026 - mean_squared_error: 0.0012 - val_loss: 0.0018 - val_acc: 0.7640 - val_mean_squared_error: 0.0018
Epoch 42/50
Epoch 00041: val_loss improved from 0.00123 to 0.00121, saving model to ./model/RMSprop_model.weights.best.hdf5
2s - loss: 0.0012 - acc: 0.8020 - mean_squared_error: 0.0012 - val_loss: 0.0012 - val_acc: 0.7640 - val_mean_squared_error: 0.0012
Epoch 43/50
Epoch 00042: val_loss did not improve
2s - loss: 0.0012 - acc: 0.7985 - mean_squared_error: 0.0012 - val_loss: 0.0012 - val_acc: 0.7617 - val_mean_squared_error: 0.0012
Epoch 44/50
Epoch 00043: val_loss did not improve
2s - loss: 0.0011 - acc: 0.8078 - mean_squared_error: 0.0011 - val_loss: 0.0013 - val_acc: 0.7757 - val_mean_squared_error: 0.0013
Epoch 45/50
Epoch 00044: val_loss did not improve
2s - loss: 0.0011 - acc: 0.8037 - mean_squared_error: 0.0011 - val_loss: 0.0013 - val_acc: 0.7757 - val_mean_squared_error: 0.0013
Epoch 46/50
Epoch 00045: val_loss improved from 0.00121 to 0.00110, saving model to ./model/RMSprop_model.weights.best.hdf5
2s - loss: 0.0011 - acc: 0.8032 - mean_squared_error: 0.0011 - val_loss: 0.0011 - val_acc: 0.7944 - val_mean_squared_error: 0.0011
Epoch 47/50
Epoch 00046: val_loss did not improve
2s - loss: 0.0011 - acc: 0.7926 - mean_squared_error: 0.0011 - val_loss: 0.0012 - val_acc: 0.7687 - val_mean_squared_error: 0.0012
Epoch 48/50
Epoch 00047: val_loss did not improve
2s - loss: 0.0011 - acc: 0.8131 - mean_squared_error: 0.0011 - val_loss: 0.0015 - val_acc: 0.7897 - val_mean_squared_error: 0.0015
Epoch 49/50
Epoch 00048: val_loss did not improve
2s - loss: 0.0010 - acc: 0.8183 - mean_squared_error: 0.0010 - val_loss: 0.0012 - val_acc: 0.7780 - val_mean_squared_error: 0.0012
Epoch 50/50
Epoch 00049: val_loss did not improve
2s - loss: 0.0010 - acc: 0.8072 - mean_squared_error: 0.0010 - val_loss: 0.0012 - val_acc: 0.7757 - val_mean_squared_error: 0.0012
Running model: bigger_base_model w/opt: Adagrad
Train on 1712 samples, validate on 428 samples
Epoch 1/50
Epoch 00000: val_loss improved from inf to 0.01305, saving model to ./model/Adagrad_model.weights.best.hdf5
3s - loss: 8.8295 - acc: 0.3651 - mean_squared_error: 8.8295 - val_loss: 0.0130 - val_acc: 0.6963 - val_mean_squared_error: 0.0130
Epoch 2/50
Epoch 00001: val_loss improved from 0.01305 to 0.00495, saving model to ./model/Adagrad_model.weights.best.hdf5
2s - loss: 0.0218 - acc: 0.4720 - mean_squared_error: 0.0218 - val_loss: 0.0050 - val_acc: 0.6963 - val_mean_squared_error: 0.0050
Epoch 3/50
Epoch 00002: val_loss did not improve
2s - loss: 0.0196 - acc: 0.5450 - mean_squared_error: 0.0196 - val_loss: 0.0101 - val_acc: 0.6963 - val_mean_squared_error: 0.0101
Epoch 4/50
Epoch 00003: val_loss did not improve
2s - loss: 0.0197 - acc: 0.5374 - mean_squared_error: 0.0197 - val_loss: 0.0097 - val_acc: 0.6963 - val_mean_squared_error: 0.0097
Epoch 5/50
Epoch 00004: val_loss did not improve
2s - loss: 0.0187 - acc: 0.5456 - mean_squared_error: 0.0187 - val_loss: 0.0089 - val_acc: 0.6963 - val_mean_squared_error: 0.0089
Epoch 6/50
Epoch 00005: val_loss did not improve
2s - loss: 0.0194 - acc: 0.5660 - mean_squared_error: 0.0194 - val_loss: 0.0067 - val_acc: 0.6963 - val_mean_squared_error: 0.0067
Epoch 7/50
Epoch 00006: val_loss did not improve
2s - loss: 0.0189 - acc: 0.5777 - mean_squared_error: 0.0189 - val_loss: 0.0058 - val_acc: 0.6963 - val_mean_squared_error: 0.0058
Epoch 8/50
Epoch 00007: val_loss did not improve
2s - loss: 0.0196 - acc: 0.5672 - mean_squared_error: 0.0196 - val_loss: 0.0060 - val_acc: 0.6963 - val_mean_squared_error: 0.0060
Epoch 9/50
Epoch 00008: val_loss improved from 0.00495 to 0.00423, saving model to ./model/Adagrad_model.weights.best.hdf5
2s - loss: 0.0179 - acc: 0.5783 - mean_squared_error: 0.0179 - val_loss: 0.0042 - val_acc: 0.6963 - val_mean_squared_error: 0.0042
Epoch 10/50
Epoch 00009: val_loss did not improve
2s - loss: 0.0181 - acc: 0.5859 - mean_squared_error: 0.0181 - val_loss: 0.0051 - val_acc: 0.6963 - val_mean_squared_error: 0.0051
Epoch 11/50
Epoch 00010: val_loss did not improve
2s - loss: 0.0179 - acc: 0.5707 - mean_squared_error: 0.0179 - val_loss: 0.0072 - val_acc: 0.6963 - val_mean_squared_error: 0.0072
Epoch 12/50
Epoch 00011: val_loss improved from 0.00423 to 0.00418, saving model to ./model/Adagrad_model.weights.best.hdf5
2s - loss: 0.0184 - acc: 0.5613 - mean_squared_error: 0.0184 - val_loss: 0.0042 - val_acc: 0.6963 - val_mean_squared_error: 0.0042
Epoch 13/50
Epoch 00012: val_loss did not improve
2s - loss: 0.0177 - acc: 0.5748 - mean_squared_error: 0.0177 - val_loss: 0.0045 - val_acc: 0.6963 - val_mean_squared_error: 0.0045
Epoch 14/50
Epoch 00013: val_loss did not improve
2s - loss: 0.0177 - acc: 0.6075 - mean_squared_error: 0.0177 - val_loss: 0.0055 - val_acc: 0.6963 - val_mean_squared_error: 0.0055
Epoch 15/50
Epoch 00014: val_loss did not improve
2s - loss: 0.0174 - acc: 0.5648 - mean_squared_error: 0.0174 - val_loss: 0.0068 - val_acc: 0.6963 - val_mean_squared_error: 0.0068
Epoch 16/50
Epoch 00015: val_loss improved from 0.00418 to 0.00345, saving model to ./model/Adagrad_model.weights.best.hdf5
2s - loss: 0.0168 - acc: 0.5666 - mean_squared_error: 0.0168 - val_loss: 0.0034 - val_acc: 0.6963 - val_mean_squared_error: 0.0034
Epoch 17/50
Epoch 00016: val_loss did not improve
2s - loss: 0.0171 - acc: 0.5549 - mean_squared_error: 0.0171 - val_loss: 0.0040 - val_acc: 0.6963 - val_mean_squared_error: 0.0040
Epoch 18/50
Epoch 00017: val_loss did not improve
2s - loss: 0.0163 - acc: 0.5736 - mean_squared_error: 0.0163 - val_loss: 0.0051 - val_acc: 0.6986 - val_mean_squared_error: 0.0051
Epoch 19/50
Epoch 00018: val_loss did not improve
2s - loss: 0.0168 - acc: 0.5730 - mean_squared_error: 0.0168 - val_loss: 0.0076 - val_acc: 0.6963 - val_mean_squared_error: 0.0076
Epoch 20/50
Epoch 00019: val_loss did not improve
2s - loss: 0.0162 - acc: 0.5789 - mean_squared_error: 0.0162 - val_loss: 0.0049 - val_acc: 0.6986 - val_mean_squared_error: 0.0049
Epoch 21/50
Epoch 00020: val_loss did not improve
2s - loss: 0.0157 - acc: 0.6016 - mean_squared_error: 0.0157 - val_loss: 0.0041 - val_acc: 0.7009 - val_mean_squared_error: 0.0041
Epoch 22/50
Epoch 00021: val_loss did not improve
2s - loss: 0.0160 - acc: 0.6057 - mean_squared_error: 0.0160 - val_loss: 0.0040 - val_acc: 0.7009 - val_mean_squared_error: 0.0040
Epoch 23/50
Epoch 00022: val_loss did not improve
2s - loss: 0.0148 - acc: 0.5847 - mean_squared_error: 0.0148 - val_loss: 0.0046 - val_acc: 0.7056 - val_mean_squared_error: 0.0046
Epoch 24/50
Epoch 00023: val_loss improved from 0.00345 to 0.00322, saving model to ./model/Adagrad_model.weights.best.hdf5
2s - loss: 0.0141 - acc: 0.5777 - mean_squared_error: 0.0141 - val_loss: 0.0032 - val_acc: 0.7056 - val_mean_squared_error: 0.0032
Epoch 25/50
Epoch 00024: val_loss improved from 0.00322 to 0.00283, saving model to ./model/Adagrad_model.weights.best.hdf5
2s - loss: 0.0144 - acc: 0.5999 - mean_squared_error: 0.0144 - val_loss: 0.0028 - val_acc: 0.7009 - val_mean_squared_error: 0.0028
Epoch 26/50
Epoch 00025: val_loss did not improve
2s - loss: 0.0138 - acc: 0.6069 - mean_squared_error: 0.0138 - val_loss: 0.0035 - val_acc: 0.7173 - val_mean_squared_error: 0.0035
Epoch 27/50
Epoch 00026: val_loss did not improve
2s - loss: 0.0140 - acc: 0.6338 - mean_squared_error: 0.0140 - val_loss: 0.0035 - val_acc: 0.7009 - val_mean_squared_error: 0.0035
Epoch 28/50
Epoch 00027: val_loss did not improve
2s - loss: 0.0136 - acc: 0.6121 - mean_squared_error: 0.0136 - val_loss: 0.0036 - val_acc: 0.7103 - val_mean_squared_error: 0.0036
Epoch 29/50
Epoch 00028: val_loss did not improve
2s - loss: 0.0139 - acc: 0.6139 - mean_squared_error: 0.0139 - val_loss: 0.0033 - val_acc: 0.7173 - val_mean_squared_error: 0.0033
Epoch 30/50
Epoch 00029: val_loss did not improve
2s - loss: 0.0134 - acc: 0.6145 - mean_squared_error: 0.0134 - val_loss: 0.0036 - val_acc: 0.7173 - val_mean_squared_error: 0.0036
Epoch 31/50
Epoch 00030: val_loss did not improve
2s - loss: 0.0137 - acc: 0.6016 - mean_squared_error: 0.0137 - val_loss: 0.0030 - val_acc: 0.7079 - val_mean_squared_error: 0.0030
Epoch 32/50
Epoch 00031: val_loss did not improve
2s - loss: 0.0132 - acc: 0.6121 - mean_squared_error: 0.0132 - val_loss: 0.0034 - val_acc: 0.7056 - val_mean_squared_error: 0.0034
Epoch 33/50
Epoch 00032: val_loss did not improve
2s - loss: 0.0134 - acc: 0.6291 - mean_squared_error: 0.0134 - val_loss: 0.0046 - val_acc: 0.7126 - val_mean_squared_error: 0.0046
Epoch 34/50
Epoch 00033: val_loss improved from 0.00283 to 0.00279, saving model to ./model/Adagrad_model.weights.best.hdf5
2s - loss: 0.0131 - acc: 0.6116 - mean_squared_error: 0.0131 - val_loss: 0.0028 - val_acc: 0.7126 - val_mean_squared_error: 0.0028
Epoch 35/50
Epoch 00034: val_loss did not improve
2s - loss: 0.0126 - acc: 0.6262 - mean_squared_error: 0.0126 - val_loss: 0.0033 - val_acc: 0.7103 - val_mean_squared_error: 0.0033
Epoch 36/50
Epoch 00035: val_loss did not improve
2s - loss: 0.0131 - acc: 0.6145 - mean_squared_error: 0.0131 - val_loss: 0.0030 - val_acc: 0.7150 - val_mean_squared_error: 0.0030
Epoch 37/50
Epoch 00036: val_loss did not improve
2s - loss: 0.0132 - acc: 0.6139 - mean_squared_error: 0.0132 - val_loss: 0.0048 - val_acc: 0.7056 - val_mean_squared_error: 0.0048
Epoch 38/50
Epoch 00037: val_loss did not improve
2s - loss: 0.0126 - acc: 0.6285 - mean_squared_error: 0.0126 - val_loss: 0.0042 - val_acc: 0.7056 - val_mean_squared_error: 0.0042
Epoch 39/50
Epoch 00038: val_loss improved from 0.00279 to 0.00278, saving model to ./model/Adagrad_model.weights.best.hdf5
2s - loss: 0.0124 - acc: 0.6279 - mean_squared_error: 0.0124 - val_loss: 0.0028 - val_acc: 0.7056 - val_mean_squared_error: 0.0028
Epoch 40/50
Epoch 00039: val_loss did not improve
2s - loss: 0.0122 - acc: 0.6425 - mean_squared_error: 0.0122 - val_loss: 0.0088 - val_acc: 0.7290 - val_mean_squared_error: 0.0088
Epoch 41/50
Epoch 00040: val_loss did not improve
2s - loss: 0.0121 - acc: 0.6273 - mean_squared_error: 0.0121 - val_loss: 0.0029 - val_acc: 0.6986 - val_mean_squared_error: 0.0029
Epoch 42/50
Epoch 00041: val_loss did not improve
2s - loss: 0.0127 - acc: 0.6086 - mean_squared_error: 0.0127 - val_loss: 0.0047 - val_acc: 0.7033 - val_mean_squared_error: 0.0047
Epoch 43/50
Epoch 00042: val_loss improved from 0.00278 to 0.00250, saving model to ./model/Adagrad_model.weights.best.hdf5
2s - loss: 0.0120 - acc: 0.6326 - mean_squared_error: 0.0120 - val_loss: 0.0025 - val_acc: 0.7056 - val_mean_squared_error: 0.0025
Epoch 44/50
Epoch 00043: val_loss did not improve
2s - loss: 0.0119 - acc: 0.6314 - mean_squared_error: 0.0119 - val_loss: 0.0036 - val_acc: 0.7079 - val_mean_squared_error: 0.0036
Epoch 45/50
Epoch 00044: val_loss improved from 0.00250 to 0.00232, saving model to ./model/Adagrad_model.weights.best.hdf5
2s - loss: 0.0118 - acc: 0.6227 - mean_squared_error: 0.0118 - val_loss: 0.0023 - val_acc: 0.7033 - val_mean_squared_error: 0.0023
Epoch 46/50
Epoch 00045: val_loss did not improve
2s - loss: 0.0118 - acc: 0.6250 - mean_squared_error: 0.0118 - val_loss: 0.0048 - val_acc: 0.7150 - val_mean_squared_error: 0.0048
Epoch 47/50
Epoch 00046: val_loss did not improve
2s - loss: 0.0117 - acc: 0.6303 - mean_squared_error: 0.0117 - val_loss: 0.0030 - val_acc: 0.7243 - val_mean_squared_error: 0.0030
Epoch 48/50
Epoch 00047: val_loss did not improve
2s - loss: 0.0118 - acc: 0.6238 - mean_squared_error: 0.0118 - val_loss: 0.0043 - val_acc: 0.7243 - val_mean_squared_error: 0.0043
Epoch 49/50
Epoch 00048: val_loss did not improve
2s - loss: 0.0117 - acc: 0.6157 - mean_squared_error: 0.0117 - val_loss: 0.0025 - val_acc: 0.7196 - val_mean_squared_error: 0.0025
Epoch 50/50
Epoch 00049: val_loss did not improve
2s - loss: 0.0114 - acc: 0.6250 - mean_squared_error: 0.0114 - val_loss: 0.0024 - val_acc: 0.7220 - val_mean_squared_error: 0.0024
Running model: bigger_base_model w/opt: Adadelta
Train on 1712 samples, validate on 428 samples
Epoch 1/50
Epoch 00000: val_loss improved from inf to 0.00761, saving model to ./model/Adadelta_model.weights.best.hdf5
4s - loss: 0.0277 - acc: 0.3989 - mean_squared_error: 0.0277 - val_loss: 0.0076 - val_acc: 0.6963 - val_mean_squared_error: 0.0076
Epoch 2/50
Epoch 00001: val_loss improved from 0.00761 to 0.00502, saving model to ./model/Adadelta_model.weights.best.hdf5
3s - loss: 0.0140 - acc: 0.4889 - mean_squared_error: 0.0140 - val_loss: 0.0050 - val_acc: 0.6963 - val_mean_squared_error: 0.0050
Epoch 3/50
Epoch 00002: val_loss did not improve
2s - loss: 0.0106 - acc: 0.5356 - mean_squared_error: 0.0106 - val_loss: 0.0070 - val_acc: 0.6963 - val_mean_squared_error: 0.0070
Epoch 4/50
Epoch 00003: val_loss improved from 0.00502 to 0.00420, saving model to ./model/Adadelta_model.weights.best.hdf5
3s - loss: 0.0093 - acc: 0.5625 - mean_squared_error: 0.0093 - val_loss: 0.0042 - val_acc: 0.6963 - val_mean_squared_error: 0.0042
Epoch 5/50
Epoch 00004: val_loss did not improve
2s - loss: 0.0080 - acc: 0.6028 - mean_squared_error: 0.0080 - val_loss: 0.0043 - val_acc: 0.6963 - val_mean_squared_error: 0.0043
Epoch 6/50
Epoch 00005: val_loss improved from 0.00420 to 0.00389, saving model to ./model/Adadelta_model.weights.best.hdf5
3s - loss: 0.0077 - acc: 0.6040 - mean_squared_error: 0.0077 - val_loss: 0.0039 - val_acc: 0.6963 - val_mean_squared_error: 0.0039
Epoch 7/50
Epoch 00006: val_loss did not improve
2s - loss: 0.0070 - acc: 0.6238 - mean_squared_error: 0.0070 - val_loss: 0.0061 - val_acc: 0.6963 - val_mean_squared_error: 0.0061
Epoch 8/50
Epoch 00007: val_loss did not improve
2s - loss: 0.0066 - acc: 0.6238 - mean_squared_error: 0.0066 - val_loss: 0.0040 - val_acc: 0.6963 - val_mean_squared_error: 0.0040
Epoch 9/50
Epoch 00008: val_loss improved from 0.00389 to 0.00364, saving model to ./model/Adadelta_model.weights.best.hdf5
3s - loss: 0.0061 - acc: 0.6367 - mean_squared_error: 0.0061 - val_loss: 0.0036 - val_acc: 0.6963 - val_mean_squared_error: 0.0036
Epoch 10/50
Epoch 00009: val_loss did not improve
2s - loss: 0.0059 - acc: 0.6589 - mean_squared_error: 0.0059 - val_loss: 0.0042 - val_acc: 0.6963 - val_mean_squared_error: 0.0042
Epoch 11/50
Epoch 00010: val_loss did not improve
2s - loss: 0.0056 - acc: 0.6688 - mean_squared_error: 0.0056 - val_loss: 0.0040 - val_acc: 0.6963 - val_mean_squared_error: 0.0040
Epoch 12/50
Epoch 00011: val_loss did not improve
2s - loss: 0.0053 - acc: 0.6641 - mean_squared_error: 0.0053 - val_loss: 0.0037 - val_acc: 0.6963 - val_mean_squared_error: 0.0037
Epoch 13/50
Epoch 00012: val_loss improved from 0.00364 to 0.00306, saving model to ./model/Adadelta_model.weights.best.hdf5
3s - loss: 0.0051 - acc: 0.6776 - mean_squared_error: 0.0051 - val_loss: 0.0031 - val_acc: 0.7009 - val_mean_squared_error: 0.0031
Epoch 14/50
Epoch 00013: val_loss did not improve
2s - loss: 0.0051 - acc: 0.6776 - mean_squared_error: 0.0051 - val_loss: 0.0032 - val_acc: 0.7056 - val_mean_squared_error: 0.0032
Epoch 15/50
Epoch 00014: val_loss improved from 0.00306 to 0.00305, saving model to ./model/Adadelta_model.weights.best.hdf5
3s - loss: 0.0049 - acc: 0.6869 - mean_squared_error: 0.0049 - val_loss: 0.0031 - val_acc: 0.7033 - val_mean_squared_error: 0.0031
Epoch 16/50
Epoch 00015: val_loss improved from 0.00305 to 0.00298, saving model to ./model/Adadelta_model.weights.best.hdf5
3s - loss: 0.0045 - acc: 0.6834 - mean_squared_error: 0.0045 - val_loss: 0.0030 - val_acc: 0.6986 - val_mean_squared_error: 0.0030
Epoch 17/50
Epoch 00016: val_loss did not improve
2s - loss: 0.0044 - acc: 0.6723 - mean_squared_error: 0.0044 - val_loss: 0.0043 - val_acc: 0.7056 - val_mean_squared_error: 0.0043
Epoch 18/50
Epoch 00017: val_loss improved from 0.00298 to 0.00263, saving model to ./model/Adadelta_model.weights.best.hdf5
3s - loss: 0.0043 - acc: 0.6893 - mean_squared_error: 0.0043 - val_loss: 0.0026 - val_acc: 0.7103 - val_mean_squared_error: 0.0026
Epoch 19/50
Epoch 00018: val_loss improved from 0.00263 to 0.00248, saving model to ./model/Adadelta_model.weights.best.hdf5
3s - loss: 0.0041 - acc: 0.6840 - mean_squared_error: 0.0041 - val_loss: 0.0025 - val_acc: 0.7079 - val_mean_squared_error: 0.0025
Epoch 20/50
Epoch 00019: val_loss improved from 0.00248 to 0.00241, saving model to ./model/Adadelta_model.weights.best.hdf5
3s - loss: 0.0040 - acc: 0.6793 - mean_squared_error: 0.0040 - val_loss: 0.0024 - val_acc: 0.7150 - val_mean_squared_error: 0.0024
Epoch 21/50
Epoch 00020: val_loss did not improve
2s - loss: 0.0039 - acc: 0.6793 - mean_squared_error: 0.0039 - val_loss: 0.0024 - val_acc: 0.7126 - val_mean_squared_error: 0.0024
Epoch 22/50
Epoch 00021: val_loss improved from 0.00241 to 0.00226, saving model to ./model/Adadelta_model.weights.best.hdf5
3s - loss: 0.0038 - acc: 0.6735 - mean_squared_error: 0.0038 - val_loss: 0.0023 - val_acc: 0.7196 - val_mean_squared_error: 0.0023
Epoch 23/50
Epoch 00022: val_loss did not improve
2s - loss: 0.0037 - acc: 0.6928 - mean_squared_error: 0.0037 - val_loss: 0.0023 - val_acc: 0.7243 - val_mean_squared_error: 0.0023
Epoch 24/50
Epoch 00023: val_loss improved from 0.00226 to 0.00223, saving model to ./model/Adadelta_model.weights.best.hdf5
3s - loss: 0.0036 - acc: 0.6881 - mean_squared_error: 0.0036 - val_loss: 0.0022 - val_acc: 0.7243 - val_mean_squared_error: 0.0022
Epoch 25/50
Epoch 00024: val_loss improved from 0.00223 to 0.00222, saving model to ./model/Adadelta_model.weights.best.hdf5
3s - loss: 0.0035 - acc: 0.7068 - mean_squared_error: 0.0035 - val_loss: 0.0022 - val_acc: 0.7173 - val_mean_squared_error: 0.0022
Epoch 26/50
Epoch 00025: val_loss did not improve
2s - loss: 0.0033 - acc: 0.6951 - mean_squared_error: 0.0033 - val_loss: 0.0024 - val_acc: 0.7220 - val_mean_squared_error: 0.0024
Epoch 27/50
Epoch 00026: val_loss improved from 0.00222 to 0.00208, saving model to ./model/Adadelta_model.weights.best.hdf5
3s - loss: 0.0034 - acc: 0.6881 - mean_squared_error: 0.0034 - val_loss: 0.0021 - val_acc: 0.7173 - val_mean_squared_error: 0.0021
Epoch 28/50
Epoch 00027: val_loss did not improve
2s - loss: 0.0033 - acc: 0.7103 - mean_squared_error: 0.0033 - val_loss: 0.0022 - val_acc: 0.7196 - val_mean_squared_error: 0.0022
Epoch 29/50
Epoch 00028: val_loss did not improve
2s - loss: 0.0032 - acc: 0.7079 - mean_squared_error: 0.0032 - val_loss: 0.0021 - val_acc: 0.7383 - val_mean_squared_error: 0.0021
Epoch 30/50
Epoch 00029: val_loss improved from 0.00208 to 0.00206, saving model to ./model/Adadelta_model.weights.best.hdf5
3s - loss: 0.0032 - acc: 0.7144 - mean_squared_error: 0.0032 - val_loss: 0.0021 - val_acc: 0.7360 - val_mean_squared_error: 0.0021
Epoch 31/50
Epoch 00030: val_loss improved from 0.00206 to 0.00202, saving model to ./model/Adadelta_model.weights.best.hdf5
3s - loss: 0.0030 - acc: 0.7021 - mean_squared_error: 0.0030 - val_loss: 0.0020 - val_acc: 0.7196 - val_mean_squared_error: 0.0020
Epoch 32/50
Epoch 00031: val_loss did not improve
2s - loss: 0.0030 - acc: 0.7144 - mean_squared_error: 0.0030 - val_loss: 0.0024 - val_acc: 0.7360 - val_mean_squared_error: 0.0024
Epoch 33/50
Epoch 00032: val_loss improved from 0.00202 to 0.00202, saving model to ./model/Adadelta_model.weights.best.hdf5
3s - loss: 0.0030 - acc: 0.7126 - mean_squared_error: 0.0030 - val_loss: 0.0020 - val_acc: 0.7360 - val_mean_squared_error: 0.0020
Epoch 34/50
Epoch 00033: val_loss improved from 0.00202 to 0.00193, saving model to ./model/Adadelta_model.weights.best.hdf5
3s - loss: 0.0029 - acc: 0.7056 - mean_squared_error: 0.0029 - val_loss: 0.0019 - val_acc: 0.7266 - val_mean_squared_error: 0.0019
Epoch 35/50
Epoch 00034: val_loss did not improve
2s - loss: 0.0029 - acc: 0.7091 - mean_squared_error: 0.0029 - val_loss: 0.0020 - val_acc: 0.7336 - val_mean_squared_error: 0.0020
Epoch 36/50
Epoch 00035: val_loss did not improve
2s - loss: 0.0028 - acc: 0.7231 - mean_squared_error: 0.0028 - val_loss: 0.0023 - val_acc: 0.7430 - val_mean_squared_error: 0.0023
Epoch 37/50
Epoch 00036: val_loss did not improve
2s - loss: 0.0027 - acc: 0.7033 - mean_squared_error: 0.0027 - val_loss: 0.0020 - val_acc: 0.7336 - val_mean_squared_error: 0.0020
Epoch 38/50
Epoch 00037: val_loss improved from 0.00193 to 0.00183, saving model to ./model/Adadelta_model.weights.best.hdf5
3s - loss: 0.0027 - acc: 0.7208 - mean_squared_error: 0.0027 - val_loss: 0.0018 - val_acc: 0.7266 - val_mean_squared_error: 0.0018
Epoch 39/50
Epoch 00038: val_loss did not improve
2s - loss: 0.0027 - acc: 0.7185 - mean_squared_error: 0.0027 - val_loss: 0.0020 - val_acc: 0.7383 - val_mean_squared_error: 0.0020
Epoch 40/50
Epoch 00039: val_loss did not improve
2s - loss: 0.0026 - acc: 0.7196 - mean_squared_error: 0.0026 - val_loss: 0.0018 - val_acc: 0.7407 - val_mean_squared_error: 0.0018
Epoch 41/50
Epoch 00040: val_loss improved from 0.00183 to 0.00173, saving model to ./model/Adadelta_model.weights.best.hdf5
3s - loss: 0.0026 - acc: 0.7173 - mean_squared_error: 0.0026 - val_loss: 0.0017 - val_acc: 0.7383 - val_mean_squared_error: 0.0017
Epoch 42/50
Epoch 00041: val_loss did not improve
2s - loss: 0.0025 - acc: 0.7138 - mean_squared_error: 0.0025 - val_loss: 0.0023 - val_acc: 0.7360 - val_mean_squared_error: 0.0023
Epoch 43/50
Epoch 00042: val_loss did not improve
2s - loss: 0.0025 - acc: 0.7261 - mean_squared_error: 0.0025 - val_loss: 0.0017 - val_acc: 0.7336 - val_mean_squared_error: 0.0017
Epoch 44/50
Epoch 00043: val_loss did not improve
2s - loss: 0.0025 - acc: 0.7208 - mean_squared_error: 0.0025 - val_loss: 0.0017 - val_acc: 0.7243 - val_mean_squared_error: 0.0017
Epoch 45/50
Epoch 00044: val_loss improved from 0.00173 to 0.00173, saving model to ./model/Adadelta_model.weights.best.hdf5
3s - loss: 0.0025 - acc: 0.7185 - mean_squared_error: 0.0025 - val_loss: 0.0017 - val_acc: 0.7407 - val_mean_squared_error: 0.0017
Epoch 46/50
Epoch 00045: val_loss did not improve
2s - loss: 0.0024 - acc: 0.7249 - mean_squared_error: 0.0024 - val_loss: 0.0018 - val_acc: 0.7360 - val_mean_squared_error: 0.0018
Epoch 47/50
Epoch 00046: val_loss did not improve
2s - loss: 0.0024 - acc: 0.7290 - mean_squared_error: 0.0024 - val_loss: 0.0019 - val_acc: 0.7336 - val_mean_squared_error: 0.0019
Epoch 48/50
Epoch 00047: val_loss improved from 0.00173 to 0.00166, saving model to ./model/Adadelta_model.weights.best.hdf5
3s - loss: 0.0024 - acc: 0.7161 - mean_squared_error: 0.0024 - val_loss: 0.0017 - val_acc: 0.7383 - val_mean_squared_error: 0.0017
Epoch 49/50
Epoch 00048: val_loss improved from 0.00166 to 0.00165, saving model to ./model/Adadelta_model.weights.best.hdf5
3s - loss: 0.0023 - acc: 0.7214 - mean_squared_error: 0.0023 - val_loss: 0.0017 - val_acc: 0.7336 - val_mean_squared_error: 0.0017
Epoch 50/50
Epoch 00049: val_loss did not improve
2s - loss: 0.0023 - acc: 0.7196 - mean_squared_error: 0.0023 - val_loss: 0.0019 - val_acc: 0.7453 - val_mean_squared_error: 0.0019
Running model: bigger_base_model w/opt: Adam
Train on 1712 samples, validate on 428 samples
Epoch 1/50
Epoch 00000: val_loss improved from inf to 0.00470, saving model to ./model/Adam_model.weights.best.hdf5
4s - loss: 0.0233 - acc: 0.4544 - mean_squared_error: 0.0233 - val_loss: 0.0047 - val_acc: 0.6963 - val_mean_squared_error: 0.0047
Epoch 2/50
Epoch 00001: val_loss improved from 0.00470 to 0.00394, saving model to ./model/Adam_model.weights.best.hdf5
3s - loss: 0.0083 - acc: 0.6005 - mean_squared_error: 0.0083 - val_loss: 0.0039 - val_acc: 0.6963 - val_mean_squared_error: 0.0039
Epoch 3/50
Epoch 00002: val_loss improved from 0.00394 to 0.00285, saving model to ./model/Adam_model.weights.best.hdf5
3s - loss: 0.0064 - acc: 0.6279 - mean_squared_error: 0.0064 - val_loss: 0.0029 - val_acc: 0.7009 - val_mean_squared_error: 0.0029
Epoch 4/50
Epoch 00003: val_loss improved from 0.00285 to 0.00249, saving model to ./model/Adam_model.weights.best.hdf5
3s - loss: 0.0053 - acc: 0.6548 - mean_squared_error: 0.0053 - val_loss: 0.0025 - val_acc: 0.7079 - val_mean_squared_error: 0.0025
Epoch 5/50
Epoch 00004: val_loss improved from 0.00249 to 0.00216, saving model to ./model/Adam_model.weights.best.hdf5
3s - loss: 0.0044 - acc: 0.6641 - mean_squared_error: 0.0044 - val_loss: 0.0022 - val_acc: 0.7079 - val_mean_squared_error: 0.0022
Epoch 6/50
Epoch 00005: val_loss did not improve
2s - loss: 0.0041 - acc: 0.6735 - mean_squared_error: 0.0041 - val_loss: 0.0037 - val_acc: 0.7290 - val_mean_squared_error: 0.0037
Epoch 7/50
Epoch 00006: val_loss improved from 0.00216 to 0.00187, saving model to ./model/Adam_model.weights.best.hdf5
3s - loss: 0.0038 - acc: 0.6799 - mean_squared_error: 0.0038 - val_loss: 0.0019 - val_acc: 0.7243 - val_mean_squared_error: 0.0019
Epoch 8/50
Epoch 00007: val_loss did not improve
2s - loss: 0.0034 - acc: 0.7039 - mean_squared_error: 0.0034 - val_loss: 0.0019 - val_acc: 0.7383 - val_mean_squared_error: 0.0019
Epoch 9/50
Epoch 00008: val_loss did not improve
2s - loss: 0.0033 - acc: 0.7027 - mean_squared_error: 0.0033 - val_loss: 0.0019 - val_acc: 0.7220 - val_mean_squared_error: 0.0019
Epoch 10/50
Epoch 00009: val_loss improved from 0.00187 to 0.00160, saving model to ./model/Adam_model.weights.best.hdf5
3s - loss: 0.0030 - acc: 0.7313 - mean_squared_error: 0.0030 - val_loss: 0.0016 - val_acc: 0.7243 - val_mean_squared_error: 0.0016
Epoch 11/50
Epoch 00010: val_loss improved from 0.00160 to 0.00159, saving model to ./model/Adam_model.weights.best.hdf5
3s - loss: 0.0029 - acc: 0.7185 - mean_squared_error: 0.0029 - val_loss: 0.0016 - val_acc: 0.7336 - val_mean_squared_error: 0.0016
Epoch 12/50
Epoch 00011: val_loss improved from 0.00159 to 0.00158, saving model to ./model/Adam_model.weights.best.hdf5
3s - loss: 0.0028 - acc: 0.7120 - mean_squared_error: 0.0028 - val_loss: 0.0016 - val_acc: 0.7710 - val_mean_squared_error: 0.0016
Epoch 13/50
Epoch 00012: val_loss did not improve
2s - loss: 0.0028 - acc: 0.7331 - mean_squared_error: 0.0028 - val_loss: 0.0016 - val_acc: 0.7710 - val_mean_squared_error: 0.0016
Epoch 14/50
Epoch 00013: val_loss did not improve
2s - loss: 0.0026 - acc: 0.7436 - mean_squared_error: 0.0026 - val_loss: 0.0019 - val_acc: 0.7710 - val_mean_squared_error: 0.0019
Epoch 15/50
Epoch 00014: val_loss did not improve
2s - loss: 0.0025 - acc: 0.7401 - mean_squared_error: 0.0025 - val_loss: 0.0018 - val_acc: 0.7523 - val_mean_squared_error: 0.0018
Epoch 16/50
Epoch 00015: val_loss improved from 0.00158 to 0.00141, saving model to ./model/Adam_model.weights.best.hdf5
3s - loss: 0.0025 - acc: 0.7319 - mean_squared_error: 0.0025 - val_loss: 0.0014 - val_acc: 0.7640 - val_mean_squared_error: 0.0014
Epoch 17/50
Epoch 00016: val_loss did not improve
2s - loss: 0.0023 - acc: 0.7389 - mean_squared_error: 0.0023 - val_loss: 0.0016 - val_acc: 0.7710 - val_mean_squared_error: 0.0016
Epoch 18/50
Epoch 00017: val_loss did not improve
2s - loss: 0.0022 - acc: 0.7389 - mean_squared_error: 0.0022 - val_loss: 0.0015 - val_acc: 0.7523 - val_mean_squared_error: 0.0015
Epoch 19/50
Epoch 00018: val_loss did not improve
2s - loss: 0.0021 - acc: 0.7529 - mean_squared_error: 0.0021 - val_loss: 0.0014 - val_acc: 0.7523 - val_mean_squared_error: 0.0014
Epoch 20/50
Epoch 00019: val_loss did not improve
2s - loss: 0.0021 - acc: 0.7523 - mean_squared_error: 0.0021 - val_loss: 0.0015 - val_acc: 0.7710 - val_mean_squared_error: 0.0015
Epoch 21/50
Epoch 00020: val_loss did not improve
2s - loss: 0.0021 - acc: 0.7588 - mean_squared_error: 0.0021 - val_loss: 0.0015 - val_acc: 0.7710 - val_mean_squared_error: 0.0015
Epoch 22/50
Epoch 00021: val_loss did not improve
2s - loss: 0.0019 - acc: 0.7570 - mean_squared_error: 0.0019 - val_loss: 0.0017 - val_acc: 0.7757 - val_mean_squared_error: 0.0017
Epoch 23/50
Epoch 00022: val_loss improved from 0.00141 to 0.00130, saving model to ./model/Adam_model.weights.best.hdf5
3s - loss: 0.0019 - acc: 0.7623 - mean_squared_error: 0.0019 - val_loss: 0.0013 - val_acc: 0.7850 - val_mean_squared_error: 0.0013
Epoch 24/50
Epoch 00023: val_loss improved from 0.00130 to 0.00129, saving model to ./model/Adam_model.weights.best.hdf5
3s - loss: 0.0019 - acc: 0.7669 - mean_squared_error: 0.0019 - val_loss: 0.0013 - val_acc: 0.7687 - val_mean_squared_error: 0.0013
Epoch 25/50
Epoch 00024: val_loss improved from 0.00129 to 0.00126, saving model to ./model/Adam_model.weights.best.hdf5
3s - loss: 0.0018 - acc: 0.7629 - mean_squared_error: 0.0018 - val_loss: 0.0013 - val_acc: 0.7640 - val_mean_squared_error: 0.0013
Epoch 26/50
Epoch 00025: val_loss did not improve
2s - loss: 0.0019 - acc: 0.7535 - mean_squared_error: 0.0019 - val_loss: 0.0014 - val_acc: 0.7874 - val_mean_squared_error: 0.0014
Epoch 27/50
Epoch 00026: val_loss improved from 0.00126 to 0.00121, saving model to ./model/Adam_model.weights.best.hdf5
3s - loss: 0.0017 - acc: 0.7646 - mean_squared_error: 0.0017 - val_loss: 0.0012 - val_acc: 0.7570 - val_mean_squared_error: 0.0012
Epoch 28/50
Epoch 00027: val_loss did not improve
2s - loss: 0.0016 - acc: 0.7792 - mean_squared_error: 0.0016 - val_loss: 0.0012 - val_acc: 0.7757 - val_mean_squared_error: 0.0012
Epoch 29/50
Epoch 00028: val_loss did not improve
2s - loss: 0.0016 - acc: 0.7763 - mean_squared_error: 0.0016 - val_loss: 0.0012 - val_acc: 0.7710 - val_mean_squared_error: 0.0012
Epoch 30/50
Epoch 00029: val_loss improved from 0.00121 to 0.00114, saving model to ./model/Adam_model.weights.best.hdf5
3s - loss: 0.0016 - acc: 0.7728 - mean_squared_error: 0.0016 - val_loss: 0.0011 - val_acc: 0.8037 - val_mean_squared_error: 0.0011
Epoch 31/50
Epoch 00030: val_loss did not improve
2s - loss: 0.0016 - acc: 0.7769 - mean_squared_error: 0.0016 - val_loss: 0.0012 - val_acc: 0.7967 - val_mean_squared_error: 0.0012
Epoch 32/50
Epoch 00031: val_loss improved from 0.00114 to 0.00114, saving model to ./model/Adam_model.weights.best.hdf5
3s - loss: 0.0016 - acc: 0.7769 - mean_squared_error: 0.0016 - val_loss: 0.0011 - val_acc: 0.7944 - val_mean_squared_error: 0.0011
Epoch 33/50
Epoch 00032: val_loss improved from 0.00114 to 0.00111, saving model to ./model/Adam_model.weights.best.hdf5
3s - loss: 0.0015 - acc: 0.7751 - mean_squared_error: 0.0015 - val_loss: 0.0011 - val_acc: 0.7967 - val_mean_squared_error: 0.0011
Epoch 34/50
Epoch 00033: val_loss did not improve
2s - loss: 0.0015 - acc: 0.7862 - mean_squared_error: 0.0015 - val_loss: 0.0011 - val_acc: 0.7991 - val_mean_squared_error: 0.0011
Epoch 35/50
Epoch 00034: val_loss did not improve
2s - loss: 0.0015 - acc: 0.7915 - mean_squared_error: 0.0015 - val_loss: 0.0012 - val_acc: 0.7897 - val_mean_squared_error: 0.0012
Epoch 36/50
Epoch 00035: val_loss did not improve
2s - loss: 0.0014 - acc: 0.7856 - mean_squared_error: 0.0014 - val_loss: 0.0012 - val_acc: 0.7921 - val_mean_squared_error: 0.0012
Epoch 37/50
Epoch 00036: val_loss did not improve
2s - loss: 0.0014 - acc: 0.7751 - mean_squared_error: 0.0014 - val_loss: 0.0012 - val_acc: 0.8037 - val_mean_squared_error: 0.0012
Epoch 38/50
Epoch 00037: val_loss improved from 0.00111 to 0.00109, saving model to ./model/Adam_model.weights.best.hdf5
3s - loss: 0.0014 - acc: 0.7751 - mean_squared_error: 0.0014 - val_loss: 0.0011 - val_acc: 0.8014 - val_mean_squared_error: 0.0011
Epoch 39/50
Epoch 00038: val_loss did not improve
2s - loss: 0.0013 - acc: 0.7821 - mean_squared_error: 0.0013 - val_loss: 0.0011 - val_acc: 0.8131 - val_mean_squared_error: 0.0011
Epoch 40/50
Epoch 00039: val_loss did not improve
2s - loss: 0.0013 - acc: 0.7961 - mean_squared_error: 0.0013 - val_loss: 0.0011 - val_acc: 0.8131 - val_mean_squared_error: 0.0011
Epoch 41/50
Epoch 00040: val_loss improved from 0.00109 to 0.00109, saving model to ./model/Adam_model.weights.best.hdf5
3s - loss: 0.0013 - acc: 0.7915 - mean_squared_error: 0.0013 - val_loss: 0.0011 - val_acc: 0.8061 - val_mean_squared_error: 0.0011
Epoch 42/50
Epoch 00041: val_loss did not improve
2s - loss: 0.0012 - acc: 0.8049 - mean_squared_error: 0.0012 - val_loss: 0.0011 - val_acc: 0.7897 - val_mean_squared_error: 0.0011
Epoch 43/50
Epoch 00042: val_loss improved from 0.00109 to 0.00106, saving model to ./model/Adam_model.weights.best.hdf5
3s - loss: 0.0013 - acc: 0.7921 - mean_squared_error: 0.0013 - val_loss: 0.0011 - val_acc: 0.7991 - val_mean_squared_error: 0.0011
Epoch 44/50
Epoch 00043: val_loss improved from 0.00106 to 0.00104, saving model to ./model/Adam_model.weights.best.hdf5
3s - loss: 0.0012 - acc: 0.8119 - mean_squared_error: 0.0012 - val_loss: 0.0010 - val_acc: 0.8248 - val_mean_squared_error: 0.0010
Epoch 45/50
Epoch 00044: val_loss did not improve
2s - loss: 0.0012 - acc: 0.8067 - mean_squared_error: 0.0012 - val_loss: 0.0011 - val_acc: 0.7874 - val_mean_squared_error: 0.0011
Epoch 46/50
Epoch 00045: val_loss improved from 0.00104 to 0.00101, saving model to ./model/Adam_model.weights.best.hdf5
3s - loss: 0.0012 - acc: 0.7996 - mean_squared_error: 0.0012 - val_loss: 0.0010 - val_acc: 0.8107 - val_mean_squared_error: 0.0010
Epoch 47/50
Epoch 00046: val_loss did not improve
2s - loss: 0.0011 - acc: 0.7880 - mean_squared_error: 0.0011 - val_loss: 0.0011 - val_acc: 0.7991 - val_mean_squared_error: 0.0011
Epoch 48/50
Epoch 00047: val_loss did not improve
2s - loss: 0.0011 - acc: 0.8037 - mean_squared_error: 0.0011 - val_loss: 0.0011 - val_acc: 0.8014 - val_mean_squared_error: 0.0011
Epoch 49/50
Epoch 00048: val_loss did not improve
2s - loss: 0.0011 - acc: 0.8008 - mean_squared_error: 0.0011 - val_loss: 0.0011 - val_acc: 0.8084 - val_mean_squared_error: 0.0011
Epoch 50/50
Epoch 00049: val_loss improved from 0.00101 to 0.00101, saving model to ./model/Adam_model.weights.best.hdf5
3s - loss: 0.0011 - acc: 0.8026 - mean_squared_error: 0.0011 - val_loss: 0.0010 - val_acc: 0.8224 - val_mean_squared_error: 0.0010
Running model: bigger_base_model w/opt: Adamax
Train on 1712 samples, validate on 428 samples
Epoch 1/50
Epoch 00000: val_loss improved from inf to 0.00483, saving model to ./model/Adamax_model.weights.best.hdf5
4s - loss: 0.0345 - acc: 0.4118 - mean_squared_error: 0.0345 - val_loss: 0.0048 - val_acc: 0.6893 - val_mean_squared_error: 0.0048
Epoch 2/50
Epoch 00001: val_loss improved from 0.00483 to 0.00428, saving model to ./model/Adamax_model.weights.best.hdf5
3s - loss: 0.0117 - acc: 0.4790 - mean_squared_error: 0.0117 - val_loss: 0.0043 - val_acc: 0.7033 - val_mean_squared_error: 0.0043
Epoch 3/50
Epoch 00002: val_loss improved from 0.00428 to 0.00411, saving model to ./model/Adamax_model.weights.best.hdf5
2s - loss: 0.0096 - acc: 0.5409 - mean_squared_error: 0.0096 - val_loss: 0.0041 - val_acc: 0.7103 - val_mean_squared_error: 0.0041
Epoch 4/50
Epoch 00003: val_loss did not improve
2s - loss: 0.0084 - acc: 0.5718 - mean_squared_error: 0.0084 - val_loss: 0.0045 - val_acc: 0.7056 - val_mean_squared_error: 0.0045
Epoch 5/50
Epoch 00004: val_loss improved from 0.00411 to 0.00276, saving model to ./model/Adamax_model.weights.best.hdf5
3s - loss: 0.0072 - acc: 0.5905 - mean_squared_error: 0.0072 - val_loss: 0.0028 - val_acc: 0.7126 - val_mean_squared_error: 0.0028
Epoch 6/50
Epoch 00005: val_loss improved from 0.00276 to 0.00254, saving model to ./model/Adamax_model.weights.best.hdf5
2s - loss: 0.0064 - acc: 0.6051 - mean_squared_error: 0.0064 - val_loss: 0.0025 - val_acc: 0.7196 - val_mean_squared_error: 0.0025
Epoch 7/50
Epoch 00006: val_loss improved from 0.00254 to 0.00217, saving model to ./model/Adamax_model.weights.best.hdf5
2s - loss: 0.0058 - acc: 0.6250 - mean_squared_error: 0.0058 - val_loss: 0.0022 - val_acc: 0.7360 - val_mean_squared_error: 0.0022
Epoch 8/50
Epoch 00007: val_loss did not improve
2s - loss: 0.0055 - acc: 0.6314 - mean_squared_error: 0.0055 - val_loss: 0.0029 - val_acc: 0.7126 - val_mean_squared_error: 0.0029
Epoch 9/50
Epoch 00008: val_loss did not improve
2s - loss: 0.0052 - acc: 0.6449 - mean_squared_error: 0.0052 - val_loss: 0.0023 - val_acc: 0.7243 - val_mean_squared_error: 0.0023
Epoch 10/50
Epoch 00009: val_loss did not improve
2s - loss: 0.0050 - acc: 0.6507 - mean_squared_error: 0.0050 - val_loss: 0.0026 - val_acc: 0.7477 - val_mean_squared_error: 0.0026
Epoch 11/50
Epoch 00010: val_loss improved from 0.00217 to 0.00212, saving model to ./model/Adamax_model.weights.best.hdf5
2s - loss: 0.0049 - acc: 0.6606 - mean_squared_error: 0.0049 - val_loss: 0.0021 - val_acc: 0.7430 - val_mean_squared_error: 0.0021
Epoch 12/50
Epoch 00011: val_loss improved from 0.00212 to 0.00186, saving model to ./model/Adamax_model.weights.best.hdf5
3s - loss: 0.0047 - acc: 0.6700 - mean_squared_error: 0.0047 - val_loss: 0.0019 - val_acc: 0.7336 - val_mean_squared_error: 0.0019
Epoch 13/50
Epoch 00012: val_loss did not improve
2s - loss: 0.0044 - acc: 0.6723 - mean_squared_error: 0.0044 - val_loss: 0.0019 - val_acc: 0.7523 - val_mean_squared_error: 0.0019
Epoch 14/50
Epoch 00013: val_loss did not improve
2s - loss: 0.0041 - acc: 0.6840 - mean_squared_error: 0.0041 - val_loss: 0.0019 - val_acc: 0.7453 - val_mean_squared_error: 0.0019
Epoch 15/50
Epoch 00014: val_loss improved from 0.00186 to 0.00169, saving model to ./model/Adamax_model.weights.best.hdf5
3s - loss: 0.0041 - acc: 0.6770 - mean_squared_error: 0.0041 - val_loss: 0.0017 - val_acc: 0.7570 - val_mean_squared_error: 0.0017
Epoch 16/50
Epoch 00015: val_loss did not improve
2s - loss: 0.0039 - acc: 0.6805 - mean_squared_error: 0.0039 - val_loss: 0.0018 - val_acc: 0.7336 - val_mean_squared_error: 0.0018
Epoch 17/50
Epoch 00016: val_loss did not improve
2s - loss: 0.0039 - acc: 0.7085 - mean_squared_error: 0.0039 - val_loss: 0.0018 - val_acc: 0.7570 - val_mean_squared_error: 0.0018
Epoch 18/50
Epoch 00017: val_loss improved from 0.00169 to 0.00151, saving model to ./model/Adamax_model.weights.best.hdf5
2s - loss: 0.0040 - acc: 0.7039 - mean_squared_error: 0.0040 - val_loss: 0.0015 - val_acc: 0.7710 - val_mean_squared_error: 0.0015
Epoch 19/50
Epoch 00018: val_loss did not improve
2s - loss: 0.0037 - acc: 0.7009 - mean_squared_error: 0.0037 - val_loss: 0.0017 - val_acc: 0.7453 - val_mean_squared_error: 0.0017
Epoch 20/50
Epoch 00019: val_loss did not improve
2s - loss: 0.0036 - acc: 0.7062 - mean_squared_error: 0.0036 - val_loss: 0.0019 - val_acc: 0.7453 - val_mean_squared_error: 0.0019
Epoch 21/50
Epoch 00020: val_loss did not improve
2s - loss: 0.0034 - acc: 0.7068 - mean_squared_error: 0.0034 - val_loss: 0.0016 - val_acc: 0.7617 - val_mean_squared_error: 0.0016
Epoch 22/50
Epoch 00021: val_loss improved from 0.00151 to 0.00147, saving model to ./model/Adamax_model.weights.best.hdf5
3s - loss: 0.0034 - acc: 0.7044 - mean_squared_error: 0.0034 - val_loss: 0.0015 - val_acc: 0.7664 - val_mean_squared_error: 0.0015
Epoch 23/50
Epoch 00022: val_loss improved from 0.00147 to 0.00144, saving model to ./model/Adamax_model.weights.best.hdf5
2s - loss: 0.0032 - acc: 0.7120 - mean_squared_error: 0.0032 - val_loss: 0.0014 - val_acc: 0.7710 - val_mean_squared_error: 0.0014
Epoch 24/50
Epoch 00023: val_loss did not improve
2s - loss: 0.0031 - acc: 0.7091 - mean_squared_error: 0.0031 - val_loss: 0.0016 - val_acc: 0.7664 - val_mean_squared_error: 0.0016
Epoch 25/50
Epoch 00024: val_loss did not improve
2s - loss: 0.0030 - acc: 0.7161 - mean_squared_error: 0.0030 - val_loss: 0.0017 - val_acc: 0.7640 - val_mean_squared_error: 0.0017
Epoch 26/50
Epoch 00025: val_loss improved from 0.00144 to 0.00138, saving model to ./model/Adamax_model.weights.best.hdf5
2s - loss: 0.0030 - acc: 0.7383 - mean_squared_error: 0.0030 - val_loss: 0.0014 - val_acc: 0.7780 - val_mean_squared_error: 0.0014
Epoch 27/50
Epoch 00026: val_loss did not improve
2s - loss: 0.0028 - acc: 0.7360 - mean_squared_error: 0.0028 - val_loss: 0.0016 - val_acc: 0.7780 - val_mean_squared_error: 0.0016
Epoch 28/50
Epoch 00027: val_loss did not improve
2s - loss: 0.0028 - acc: 0.7196 - mean_squared_error: 0.0028 - val_loss: 0.0014 - val_acc: 0.7757 - val_mean_squared_error: 0.0014
Epoch 29/50
Epoch 00028: val_loss did not improve
2s - loss: 0.0028 - acc: 0.7348 - mean_squared_error: 0.0028 - val_loss: 0.0014 - val_acc: 0.7640 - val_mean_squared_error: 0.0014
Epoch 30/50
Epoch 00029: val_loss improved from 0.00138 to 0.00131, saving model to ./model/Adamax_model.weights.best.hdf5
2s - loss: 0.0027 - acc: 0.7301 - mean_squared_error: 0.0027 - val_loss: 0.0013 - val_acc: 0.7664 - val_mean_squared_error: 0.0013
Epoch 31/50
Epoch 00030: val_loss did not improve
2s - loss: 0.0025 - acc: 0.7558 - mean_squared_error: 0.0025 - val_loss: 0.0015 - val_acc: 0.7664 - val_mean_squared_error: 0.0015
Epoch 32/50
Epoch 00031: val_loss did not improve
2s - loss: 0.0026 - acc: 0.7430 - mean_squared_error: 0.0026 - val_loss: 0.0013 - val_acc: 0.7640 - val_mean_squared_error: 0.0013
Epoch 33/50
Epoch 00032: val_loss did not improve
2s - loss: 0.0024 - acc: 0.7383 - mean_squared_error: 0.0024 - val_loss: 0.0014 - val_acc: 0.7570 - val_mean_squared_error: 0.0014
Epoch 34/50
Epoch 00033: val_loss did not improve
2s - loss: 0.0024 - acc: 0.7395 - mean_squared_error: 0.0024 - val_loss: 0.0014 - val_acc: 0.7570 - val_mean_squared_error: 0.0014
Epoch 35/50
Epoch 00034: val_loss did not improve
2s - loss: 0.0023 - acc: 0.7593 - mean_squared_error: 0.0023 - val_loss: 0.0013 - val_acc: 0.7827 - val_mean_squared_error: 0.0013
Epoch 36/50
Epoch 00035: val_loss did not improve
2s - loss: 0.0024 - acc: 0.7389 - mean_squared_error: 0.0024 - val_loss: 0.0014 - val_acc: 0.7547 - val_mean_squared_error: 0.0014
Epoch 37/50
Epoch 00036: val_loss did not improve
2s - loss: 0.0022 - acc: 0.7500 - mean_squared_error: 0.0022 - val_loss: 0.0014 - val_acc: 0.7780 - val_mean_squared_error: 0.0014
Epoch 38/50
Epoch 00037: val_loss did not improve
2s - loss: 0.0022 - acc: 0.7500 - mean_squared_error: 0.0022 - val_loss: 0.0014 - val_acc: 0.7827 - val_mean_squared_error: 0.0014
Epoch 39/50
Epoch 00038: val_loss improved from 0.00131 to 0.00127, saving model to ./model/Adamax_model.weights.best.hdf5
2s - loss: 0.0021 - acc: 0.7518 - mean_squared_error: 0.0021 - val_loss: 0.0013 - val_acc: 0.7874 - val_mean_squared_error: 0.0013
Epoch 40/50
Epoch 00039: val_loss improved from 0.00127 to 0.00119, saving model to ./model/Adamax_model.weights.best.hdf5
2s - loss: 0.0021 - acc: 0.7576 - mean_squared_error: 0.0021 - val_loss: 0.0012 - val_acc: 0.7687 - val_mean_squared_error: 0.0012
Epoch 41/50
Epoch 00040: val_loss did not improve
2s - loss: 0.0019 - acc: 0.7523 - mean_squared_error: 0.0019 - val_loss: 0.0012 - val_acc: 0.7687 - val_mean_squared_error: 0.0012
Epoch 42/50
Epoch 00041: val_loss did not improve
2s - loss: 0.0019 - acc: 0.7769 - mean_squared_error: 0.0019 - val_loss: 0.0014 - val_acc: 0.7850 - val_mean_squared_error: 0.0014
Epoch 43/50
Epoch 00042: val_loss did not improve
2s - loss: 0.0019 - acc: 0.7518 - mean_squared_error: 0.0019 - val_loss: 0.0013 - val_acc: 0.7687 - val_mean_squared_error: 0.0013
Epoch 44/50
Epoch 00043: val_loss did not improve
2s - loss: 0.0018 - acc: 0.7710 - mean_squared_error: 0.0018 - val_loss: 0.0014 - val_acc: 0.7780 - val_mean_squared_error: 0.0014
Epoch 45/50
Epoch 00044: val_loss did not improve
2s - loss: 0.0018 - acc: 0.7693 - mean_squared_error: 0.0018 - val_loss: 0.0013 - val_acc: 0.7804 - val_mean_squared_error: 0.0013
Epoch 46/50
Epoch 00045: val_loss did not improve
2s - loss: 0.0017 - acc: 0.7681 - mean_squared_error: 0.0017 - val_loss: 0.0012 - val_acc: 0.7944 - val_mean_squared_error: 0.0012
Epoch 47/50
Epoch 00046: val_loss did not improve
2s - loss: 0.0017 - acc: 0.7716 - mean_squared_error: 0.0017 - val_loss: 0.0012 - val_acc: 0.7897 - val_mean_squared_error: 0.0012
Epoch 48/50
Epoch 00047: val_loss did not improve
2s - loss: 0.0016 - acc: 0.7915 - mean_squared_error: 0.0016 - val_loss: 0.0014 - val_acc: 0.8037 - val_mean_squared_error: 0.0014
Epoch 49/50
Epoch 00048: val_loss did not improve
2s - loss: 0.0016 - acc: 0.7745 - mean_squared_error: 0.0016 - val_loss: 0.0017 - val_acc: 0.7804 - val_mean_squared_error: 0.0017
Epoch 50/50
Epoch 00049: val_loss improved from 0.00119 to 0.00119, saving model to ./model/Adamax_model.weights.best.hdf5
2s - loss: 0.0016 - acc: 0.7880 - mean_squared_error: 0.0016 - val_loss: 0.0012 - val_acc: 0.7897 - val_mean_squared_error: 0.0012
Running model: bigger_base_model w/opt: Nadam
Train on 1712 samples, validate on 428 samples
Epoch 1/50
Epoch 00000: val_loss improved from inf to 0.00923, saving model to ./model/Nadam_model.weights.best.hdf5
4s - loss: 0.1205 - acc: 0.4013 - mean_squared_error: 0.1205 - val_loss: 0.0092 - val_acc: 0.6963 - val_mean_squared_error: 0.0092
Epoch 2/50
Epoch 00001: val_loss improved from 0.00923 to 0.00519, saving model to ./model/Nadam_model.weights.best.hdf5
3s - loss: 0.0138 - acc: 0.5169 - mean_squared_error: 0.0138 - val_loss: 0.0052 - val_acc: 0.6963 - val_mean_squared_error: 0.0052
Epoch 3/50
Epoch 00002: val_loss did not improve
2s - loss: 0.0106 - acc: 0.5543 - mean_squared_error: 0.0106 - val_loss: 0.0094 - val_acc: 0.6963 - val_mean_squared_error: 0.0094
Epoch 4/50
Epoch 00003: val_loss did not improve
2s - loss: 0.0095 - acc: 0.5970 - mean_squared_error: 0.0095 - val_loss: 0.0074 - val_acc: 0.6963 - val_mean_squared_error: 0.0074
Epoch 5/50
Epoch 00004: val_loss improved from 0.00519 to 0.00326, saving model to ./model/Nadam_model.weights.best.hdf5
3s - loss: 0.0081 - acc: 0.6016 - mean_squared_error: 0.0081 - val_loss: 0.0033 - val_acc: 0.6963 - val_mean_squared_error: 0.0033
Epoch 6/50
Epoch 00005: val_loss improved from 0.00326 to 0.00294, saving model to ./model/Nadam_model.weights.best.hdf5
3s - loss: 0.0069 - acc: 0.6197 - mean_squared_error: 0.0069 - val_loss: 0.0029 - val_acc: 0.6986 - val_mean_squared_error: 0.0029
Epoch 7/50
Epoch 00006: val_loss improved from 0.00294 to 0.00250, saving model to ./model/Nadam_model.weights.best.hdf5
3s - loss: 0.0067 - acc: 0.6338 - mean_squared_error: 0.0067 - val_loss: 0.0025 - val_acc: 0.7196 - val_mean_squared_error: 0.0025
Epoch 8/50
Epoch 00007: val_loss did not improve
2s - loss: 0.0059 - acc: 0.6472 - mean_squared_error: 0.0059 - val_loss: 0.0025 - val_acc: 0.7313 - val_mean_squared_error: 0.0025
Epoch 9/50
Epoch 00008: val_loss did not improve
2s - loss: 0.0056 - acc: 0.6612 - mean_squared_error: 0.0056 - val_loss: 0.0073 - val_acc: 0.7243 - val_mean_squared_error: 0.0073
Epoch 10/50
Epoch 00009: val_loss did not improve
2s - loss: 0.0050 - acc: 0.6828 - mean_squared_error: 0.0050 - val_loss: 0.0026 - val_acc: 0.7570 - val_mean_squared_error: 0.0026
Epoch 11/50
Epoch 00010: val_loss improved from 0.00250 to 0.00183, saving model to ./model/Nadam_model.weights.best.hdf5
3s - loss: 0.0047 - acc: 0.6782 - mean_squared_error: 0.0047 - val_loss: 0.0018 - val_acc: 0.7710 - val_mean_squared_error: 0.0018
Epoch 12/50
Epoch 00011: val_loss did not improve
2s - loss: 0.0044 - acc: 0.6846 - mean_squared_error: 0.0044 - val_loss: 0.0022 - val_acc: 0.7500 - val_mean_squared_error: 0.0022
Epoch 13/50
Epoch 00012: val_loss did not improve
2s - loss: 0.0041 - acc: 0.6857 - mean_squared_error: 0.0041 - val_loss: 0.0021 - val_acc: 0.7430 - val_mean_squared_error: 0.0021
Epoch 14/50
Epoch 00013: val_loss did not improve
2s - loss: 0.0040 - acc: 0.6834 - mean_squared_error: 0.0040 - val_loss: 0.0021 - val_acc: 0.7593 - val_mean_squared_error: 0.0021
Epoch 15/50
Epoch 00014: val_loss improved from 0.00183 to 0.00167, saving model to ./model/Nadam_model.weights.best.hdf5
3s - loss: 0.0037 - acc: 0.6869 - mean_squared_error: 0.0037 - val_loss: 0.0017 - val_acc: 0.7593 - val_mean_squared_error: 0.0017
Epoch 16/50
Epoch 00015: val_loss did not improve
2s - loss: 0.0034 - acc: 0.6998 - mean_squared_error: 0.0034 - val_loss: 0.0017 - val_acc: 0.7570 - val_mean_squared_error: 0.0017
Epoch 17/50
Epoch 00016: val_loss did not improve
2s - loss: 0.0032 - acc: 0.7050 - mean_squared_error: 0.0032 - val_loss: 0.0018 - val_acc: 0.7500 - val_mean_squared_error: 0.0018
Epoch 18/50
Epoch 00017: val_loss did not improve
2s - loss: 0.0031 - acc: 0.7278 - mean_squared_error: 0.0031 - val_loss: 0.0026 - val_acc: 0.7150 - val_mean_squared_error: 0.0026
Epoch 19/50
Epoch 00018: val_loss did not improve
2s - loss: 0.0029 - acc: 0.7114 - mean_squared_error: 0.0029 - val_loss: 0.0022 - val_acc: 0.7500 - val_mean_squared_error: 0.0022
Epoch 20/50
Epoch 00019: val_loss did not improve
2s - loss: 0.0027 - acc: 0.7284 - mean_squared_error: 0.0027 - val_loss: 0.0017 - val_acc: 0.7523 - val_mean_squared_error: 0.0017
Epoch 21/50
Epoch 00020: val_loss did not improve
2s - loss: 0.0027 - acc: 0.7196 - mean_squared_error: 0.0027 - val_loss: 0.0020 - val_acc: 0.7850 - val_mean_squared_error: 0.0020
Epoch 22/50
Epoch 00021: val_loss did not improve
2s - loss: 0.0025 - acc: 0.7278 - mean_squared_error: 0.0025 - val_loss: 0.0017 - val_acc: 0.7734 - val_mean_squared_error: 0.0017
Epoch 23/50
Epoch 00022: val_loss improved from 0.00167 to 0.00137, saving model to ./model/Nadam_model.weights.best.hdf5
3s - loss: 0.0024 - acc: 0.7407 - mean_squared_error: 0.0024 - val_loss: 0.0014 - val_acc: 0.7757 - val_mean_squared_error: 0.0014
Epoch 24/50
Epoch 00023: val_loss did not improve
2s - loss: 0.0023 - acc: 0.7383 - mean_squared_error: 0.0023 - val_loss: 0.0015 - val_acc: 0.7664 - val_mean_squared_error: 0.0015
Epoch 25/50
Epoch 00024: val_loss did not improve
2s - loss: 0.0022 - acc: 0.7436 - mean_squared_error: 0.0022 - val_loss: 0.0027 - val_acc: 0.7336 - val_mean_squared_error: 0.0027
Epoch 26/50
Epoch 00025: val_loss improved from 0.00137 to 0.00135, saving model to ./model/Nadam_model.weights.best.hdf5
3s - loss: 0.0021 - acc: 0.7588 - mean_squared_error: 0.0021 - val_loss: 0.0014 - val_acc: 0.7827 - val_mean_squared_error: 0.0014
Epoch 27/50
Epoch 00026: val_loss did not improve
2s - loss: 0.0020 - acc: 0.7512 - mean_squared_error: 0.0020 - val_loss: 0.0016 - val_acc: 0.7664 - val_mean_squared_error: 0.0016
Epoch 28/50
Epoch 00027: val_loss improved from 0.00135 to 0.00127, saving model to ./model/Nadam_model.weights.best.hdf5
3s - loss: 0.0019 - acc: 0.7675 - mean_squared_error: 0.0019 - val_loss: 0.0013 - val_acc: 0.8037 - val_mean_squared_error: 0.0013
Epoch 29/50
Epoch 00028: val_loss did not improve
2s - loss: 0.0019 - acc: 0.7716 - mean_squared_error: 0.0019 - val_loss: 0.0013 - val_acc: 0.7944 - val_mean_squared_error: 0.0013
Epoch 30/50
Epoch 00029: val_loss did not improve
2s - loss: 0.0018 - acc: 0.7640 - mean_squared_error: 0.0018 - val_loss: 0.0015 - val_acc: 0.7804 - val_mean_squared_error: 0.0015
Epoch 31/50
Epoch 00030: val_loss did not improve
2s - loss: 0.0018 - acc: 0.7710 - mean_squared_error: 0.0018 - val_loss: 0.0014 - val_acc: 0.8014 - val_mean_squared_error: 0.0014
Epoch 32/50
Epoch 00031: val_loss did not improve
2s - loss: 0.0017 - acc: 0.7576 - mean_squared_error: 0.0017 - val_loss: 0.0018 - val_acc: 0.7617 - val_mean_squared_error: 0.0018
Epoch 33/50
Epoch 00032: val_loss did not improve
2s - loss: 0.0016 - acc: 0.7798 - mean_squared_error: 0.0016 - val_loss: 0.0013 - val_acc: 0.7804 - val_mean_squared_error: 0.0013
Epoch 34/50
Epoch 00033: val_loss improved from 0.00127 to 0.00124, saving model to ./model/Nadam_model.weights.best.hdf5
3s - loss: 0.0016 - acc: 0.7704 - mean_squared_error: 0.0016 - val_loss: 0.0012 - val_acc: 0.7874 - val_mean_squared_error: 0.0012
Epoch 35/50
Epoch 00034: val_loss did not improve
2s - loss: 0.0016 - acc: 0.7646 - mean_squared_error: 0.0016 - val_loss: 0.0013 - val_acc: 0.7500 - val_mean_squared_error: 0.0013
Epoch 36/50
Epoch 00035: val_loss did not improve
2s - loss: 0.0019 - acc: 0.7658 - mean_squared_error: 0.0019 - val_loss: 0.0014 - val_acc: 0.7687 - val_mean_squared_error: 0.0014
Epoch 37/50
Epoch 00036: val_loss did not improve
2s - loss: 0.0016 - acc: 0.7652 - mean_squared_error: 0.0016 - val_loss: 0.0013 - val_acc: 0.7944 - val_mean_squared_error: 0.0013
Epoch 38/50
Epoch 00037: val_loss improved from 0.00124 to 0.00120, saving model to ./model/Nadam_model.weights.best.hdf5
3s - loss: 0.0014 - acc: 0.7722 - mean_squared_error: 0.0014 - val_loss: 0.0012 - val_acc: 0.7921 - val_mean_squared_error: 0.0012
Epoch 39/50
Epoch 00038: val_loss did not improve
2s - loss: 0.0014 - acc: 0.7745 - mean_squared_error: 0.0014 - val_loss: 0.0013 - val_acc: 0.7897 - val_mean_squared_error: 0.0013
Epoch 40/50
Epoch 00039: val_loss improved from 0.00120 to 0.00116, saving model to ./model/Nadam_model.weights.best.hdf5
3s - loss: 0.0014 - acc: 0.7850 - mean_squared_error: 0.0014 - val_loss: 0.0012 - val_acc: 0.7921 - val_mean_squared_error: 0.0012
Epoch 41/50
Epoch 00040: val_loss did not improve
2s - loss: 0.0013 - acc: 0.7903 - mean_squared_error: 0.0013 - val_loss: 0.0012 - val_acc: 0.7921 - val_mean_squared_error: 0.0012
Epoch 42/50
Epoch 00041: val_loss did not improve
2s - loss: 0.0013 - acc: 0.7932 - mean_squared_error: 0.0013 - val_loss: 0.0013 - val_acc: 0.7734 - val_mean_squared_error: 0.0013
Epoch 43/50
Epoch 00042: val_loss did not improve
2s - loss: 0.0013 - acc: 0.7775 - mean_squared_error: 0.0013 - val_loss: 0.0012 - val_acc: 0.7780 - val_mean_squared_error: 0.0012
Epoch 44/50
Epoch 00043: val_loss did not improve
2s - loss: 0.0012 - acc: 0.7839 - mean_squared_error: 0.0012 - val_loss: 0.0016 - val_acc: 0.7687 - val_mean_squared_error: 0.0016
Epoch 45/50
Epoch 00044: val_loss did not improve
2s - loss: 0.0012 - acc: 0.7956 - mean_squared_error: 0.0012 - val_loss: 0.0013 - val_acc: 0.7874 - val_mean_squared_error: 0.0013
Epoch 46/50
Epoch 00045: val_loss improved from 0.00116 to 0.00115, saving model to ./model/Nadam_model.weights.best.hdf5
3s - loss: 0.0012 - acc: 0.7821 - mean_squared_error: 0.0012 - val_loss: 0.0011 - val_acc: 0.7921 - val_mean_squared_error: 0.0011
Epoch 47/50
Epoch 00046: val_loss did not improve
2s - loss: 0.0012 - acc: 0.7897 - mean_squared_error: 0.0012 - val_loss: 0.0012 - val_acc: 0.7991 - val_mean_squared_error: 0.0012
Epoch 48/50
Epoch 00047: val_loss did not improve
2s - loss: 0.0012 - acc: 0.8026 - mean_squared_error: 0.0012 - val_loss: 0.0013 - val_acc: 0.7897 - val_mean_squared_error: 0.0013
Epoch 49/50
Epoch 00048: val_loss did not improve
2s - loss: 0.0012 - acc: 0.7979 - mean_squared_error: 0.0012 - val_loss: 0.0012 - val_acc: 0.7921 - val_mean_squared_error: 0.0012
Epoch 50/50
Epoch 00049: val_loss did not improve
2s - loss: 0.0011 - acc: 0.8119 - mean_squared_error: 0.0011 - val_loss: 0.0012 - val_acc: 0.7897 - val_mean_squared_error: 0.0012
Running model: dropout_base_model w/opt: SGD
Train on 1712 samples, validate on 428 samples
Epoch 1/50
Epoch 00000: val_loss improved from inf to 0.04077, saving model to ./model/SGD_model.weights.best.hdf5
3s - loss: 0.0746 - acc: 0.3037 - mean_squared_error: 0.0746 - val_loss: 0.0408 - val_acc: 0.6776 - val_mean_squared_error: 0.0408
Epoch 2/50
Epoch 00001: val_loss improved from 0.04077 to 0.03774, saving model to ./model/SGD_model.weights.best.hdf5
1s - loss: 0.0392 - acc: 0.3370 - mean_squared_error: 0.0392 - val_loss: 0.0377 - val_acc: 0.6963 - val_mean_squared_error: 0.0377
Epoch 3/50
Epoch 00002: val_loss improved from 0.03774 to 0.03530, saving model to ./model/SGD_model.weights.best.hdf5
1s - loss: 0.0332 - acc: 0.3662 - mean_squared_error: 0.0332 - val_loss: 0.0353 - val_acc: 0.6963 - val_mean_squared_error: 0.0353
Epoch 4/50
Epoch 00003: val_loss improved from 0.03530 to 0.03400, saving model to ./model/SGD_model.weights.best.hdf5
1s - loss: 0.0298 - acc: 0.3843 - mean_squared_error: 0.0298 - val_loss: 0.0340 - val_acc: 0.6963 - val_mean_squared_error: 0.0340
Epoch 5/50
Epoch 00004: val_loss improved from 0.03400 to 0.03300, saving model to ./model/SGD_model.weights.best.hdf5
1s - loss: 0.0274 - acc: 0.3949 - mean_squared_error: 0.0274 - val_loss: 0.0330 - val_acc: 0.6916 - val_mean_squared_error: 0.0330
Epoch 6/50
Epoch 00005: val_loss improved from 0.03300 to 0.03106, saving model to ./model/SGD_model.weights.best.hdf5
1s - loss: 0.0255 - acc: 0.4036 - mean_squared_error: 0.0255 - val_loss: 0.0311 - val_acc: 0.6986 - val_mean_squared_error: 0.0311
Epoch 7/50
Epoch 00006: val_loss improved from 0.03106 to 0.03021, saving model to ./model/SGD_model.weights.best.hdf5
1s - loss: 0.0236 - acc: 0.3972 - mean_squared_error: 0.0236 - val_loss: 0.0302 - val_acc: 0.6986 - val_mean_squared_error: 0.0302
Epoch 8/50
Epoch 00007: val_loss improved from 0.03021 to 0.02770, saving model to ./model/SGD_model.weights.best.hdf5
1s - loss: 0.0224 - acc: 0.3960 - mean_squared_error: 0.0224 - val_loss: 0.0277 - val_acc: 0.6986 - val_mean_squared_error: 0.0277
Epoch 9/50
Epoch 00008: val_loss improved from 0.02770 to 0.02688, saving model to ./model/SGD_model.weights.best.hdf5
1s - loss: 0.0213 - acc: 0.4153 - mean_squared_error: 0.0213 - val_loss: 0.0269 - val_acc: 0.6963 - val_mean_squared_error: 0.0269
Epoch 10/50
Epoch 00009: val_loss improved from 0.02688 to 0.02584, saving model to ./model/SGD_model.weights.best.hdf5
1s - loss: 0.0202 - acc: 0.4398 - mean_squared_error: 0.0202 - val_loss: 0.0258 - val_acc: 0.6986 - val_mean_squared_error: 0.0258
Epoch 11/50
Epoch 00010: val_loss improved from 0.02584 to 0.02379, saving model to ./model/SGD_model.weights.best.hdf5
1s - loss: 0.0194 - acc: 0.4439 - mean_squared_error: 0.0194 - val_loss: 0.0238 - val_acc: 0.6986 - val_mean_squared_error: 0.0238
Epoch 12/50
Epoch 00011: val_loss improved from 0.02379 to 0.02259, saving model to ./model/SGD_model.weights.best.hdf5
1s - loss: 0.0183 - acc: 0.4346 - mean_squared_error: 0.0183 - val_loss: 0.0226 - val_acc: 0.6986 - val_mean_squared_error: 0.0226
Epoch 13/50
Epoch 00012: val_loss improved from 0.02259 to 0.02191, saving model to ./model/SGD_model.weights.best.hdf5
1s - loss: 0.0178 - acc: 0.4451 - mean_squared_error: 0.0178 - val_loss: 0.0219 - val_acc: 0.6986 - val_mean_squared_error: 0.0219
Epoch 14/50
Epoch 00013: val_loss improved from 0.02191 to 0.02069, saving model to ./model/SGD_model.weights.best.hdf5
1s - loss: 0.0171 - acc: 0.4492 - mean_squared_error: 0.0171 - val_loss: 0.0207 - val_acc: 0.6986 - val_mean_squared_error: 0.0207
Epoch 15/50
Epoch 00014: val_loss did not improve
1s - loss: 0.0166 - acc: 0.4363 - mean_squared_error: 0.0166 - val_loss: 0.0207 - val_acc: 0.6986 - val_mean_squared_error: 0.0207
Epoch 16/50
Epoch 00015: val_loss improved from 0.02069 to 0.01867, saving model to ./model/SGD_model.weights.best.hdf5
1s - loss: 0.0158 - acc: 0.4486 - mean_squared_error: 0.0158 - val_loss: 0.0187 - val_acc: 0.6986 - val_mean_squared_error: 0.0187
Epoch 17/50
Epoch 00016: val_loss improved from 0.01867 to 0.01818, saving model to ./model/SGD_model.weights.best.hdf5
1s - loss: 0.0154 - acc: 0.4544 - mean_squared_error: 0.0154 - val_loss: 0.0182 - val_acc: 0.6986 - val_mean_squared_error: 0.0182
Epoch 18/50
Epoch 00017: val_loss improved from 0.01818 to 0.01765, saving model to ./model/SGD_model.weights.best.hdf5
1s - loss: 0.0153 - acc: 0.4457 - mean_squared_error: 0.0153 - val_loss: 0.0177 - val_acc: 0.6986 - val_mean_squared_error: 0.0177
Epoch 19/50
Epoch 00018: val_loss did not improve
1s - loss: 0.0146 - acc: 0.4626 - mean_squared_error: 0.0146 - val_loss: 0.0177 - val_acc: 0.6986 - val_mean_squared_error: 0.0177
Epoch 20/50
Epoch 00019: val_loss improved from 0.01765 to 0.01664, saving model to ./model/SGD_model.weights.best.hdf5
1s - loss: 0.0144 - acc: 0.4556 - mean_squared_error: 0.0144 - val_loss: 0.0166 - val_acc: 0.6986 - val_mean_squared_error: 0.0166
Epoch 21/50
Epoch 00020: val_loss improved from 0.01664 to 0.01632, saving model to ./model/SGD_model.weights.best.hdf5
1s - loss: 0.0140 - acc: 0.4655 - mean_squared_error: 0.0140 - val_loss: 0.0163 - val_acc: 0.6986 - val_mean_squared_error: 0.0163
Epoch 22/50
Epoch 00021: val_loss improved from 0.01632 to 0.01557, saving model to ./model/SGD_model.weights.best.hdf5
1s - loss: 0.0136 - acc: 0.4614 - mean_squared_error: 0.0136 - val_loss: 0.0156 - val_acc: 0.6963 - val_mean_squared_error: 0.0156
Epoch 23/50
Epoch 00022: val_loss improved from 0.01557 to 0.01506, saving model to ./model/SGD_model.weights.best.hdf5
1s - loss: 0.0136 - acc: 0.4825 - mean_squared_error: 0.0136 - val_loss: 0.0151 - val_acc: 0.6963 - val_mean_squared_error: 0.0151
Epoch 24/50
Epoch 00023: val_loss improved from 0.01506 to 0.01445, saving model to ./model/SGD_model.weights.best.hdf5
1s - loss: 0.0133 - acc: 0.4731 - mean_squared_error: 0.0133 - val_loss: 0.0144 - val_acc: 0.6963 - val_mean_squared_error: 0.0144
Epoch 25/50
Epoch 00024: val_loss did not improve
1s - loss: 0.0129 - acc: 0.5146 - mean_squared_error: 0.0129 - val_loss: 0.0147 - val_acc: 0.6963 - val_mean_squared_error: 0.0147
Epoch 26/50
Epoch 00025: val_loss did not improve
1s - loss: 0.0130 - acc: 0.4749 - mean_squared_error: 0.0130 - val_loss: 0.0145 - val_acc: 0.6963 - val_mean_squared_error: 0.0145
Epoch 27/50
Epoch 00026: val_loss improved from 0.01445 to 0.01394, saving model to ./model/SGD_model.weights.best.hdf5
1s - loss: 0.0125 - acc: 0.5093 - mean_squared_error: 0.0125 - val_loss: 0.0139 - val_acc: 0.6963 - val_mean_squared_error: 0.0139
Epoch 28/50
Epoch 00027: val_loss improved from 0.01394 to 0.01328, saving model to ./model/SGD_model.weights.best.hdf5
1s - loss: 0.0124 - acc: 0.4988 - mean_squared_error: 0.0124 - val_loss: 0.0133 - val_acc: 0.6963 - val_mean_squared_error: 0.0133
Epoch 29/50
Epoch 00028: val_loss did not improve
1s - loss: 0.0123 - acc: 0.5058 - mean_squared_error: 0.0123 - val_loss: 0.0138 - val_acc: 0.6963 - val_mean_squared_error: 0.0138
Epoch 30/50
Epoch 00029: val_loss improved from 0.01328 to 0.01308, saving model to ./model/SGD_model.weights.best.hdf5
1s - loss: 0.0122 - acc: 0.5000 - mean_squared_error: 0.0122 - val_loss: 0.0131 - val_acc: 0.6963 - val_mean_squared_error: 0.0131
Epoch 31/50
Epoch 00030: val_loss improved from 0.01308 to 0.01297, saving model to ./model/SGD_model.weights.best.hdf5
1s - loss: 0.0121 - acc: 0.5088 - mean_squared_error: 0.0121 - val_loss: 0.0130 - val_acc: 0.6963 - val_mean_squared_error: 0.0130
Epoch 32/50
Epoch 00031: val_loss improved from 0.01297 to 0.01205, saving model to ./model/SGD_model.weights.best.hdf5
1s - loss: 0.0119 - acc: 0.5041 - mean_squared_error: 0.0119 - val_loss: 0.0121 - val_acc: 0.6963 - val_mean_squared_error: 0.0121
Epoch 33/50
Epoch 00032: val_loss did not improve
1s - loss: 0.0118 - acc: 0.4877 - mean_squared_error: 0.0118 - val_loss: 0.0124 - val_acc: 0.6963 - val_mean_squared_error: 0.0124
Epoch 34/50
Epoch 00033: val_loss did not improve
1s - loss: 0.0116 - acc: 0.5076 - mean_squared_error: 0.0116 - val_loss: 0.0125 - val_acc: 0.6963 - val_mean_squared_error: 0.0125
Epoch 35/50
Epoch 00034: val_loss did not improve
1s - loss: 0.0116 - acc: 0.5321 - mean_squared_error: 0.0116 - val_loss: 0.0125 - val_acc: 0.6963 - val_mean_squared_error: 0.0125
Epoch 36/50
Epoch 00035: val_loss improved from 0.01205 to 0.01152, saving model to ./model/SGD_model.weights.best.hdf5
1s - loss: 0.0115 - acc: 0.5152 - mean_squared_error: 0.0115 - val_loss: 0.0115 - val_acc: 0.6963 - val_mean_squared_error: 0.0115
Epoch 37/50
Epoch 00036: val_loss did not improve
1s - loss: 0.0115 - acc: 0.5169 - mean_squared_error: 0.0115 - val_loss: 0.0122 - val_acc: 0.6963 - val_mean_squared_error: 0.0122
Epoch 38/50
Epoch 00037: val_loss did not improve
1s - loss: 0.0113 - acc: 0.5076 - mean_squared_error: 0.0113 - val_loss: 0.0116 - val_acc: 0.6963 - val_mean_squared_error: 0.0116
Epoch 39/50
Epoch 00038: val_loss improved from 0.01152 to 0.01124, saving model to ./model/SGD_model.weights.best.hdf5
1s - loss: 0.0112 - acc: 0.5175 - mean_squared_error: 0.0112 - val_loss: 0.0112 - val_acc: 0.6963 - val_mean_squared_error: 0.0112
Epoch 40/50
Epoch 00039: val_loss improved from 0.01124 to 0.01114, saving model to ./model/SGD_model.weights.best.hdf5
1s - loss: 0.0110 - acc: 0.5286 - mean_squared_error: 0.0110 - val_loss: 0.0111 - val_acc: 0.6963 - val_mean_squared_error: 0.0111
Epoch 41/50
Epoch 00040: val_loss improved from 0.01114 to 0.01110, saving model to ./model/SGD_model.weights.best.hdf5
1s - loss: 0.0110 - acc: 0.5386 - mean_squared_error: 0.0110 - val_loss: 0.0111 - val_acc: 0.6963 - val_mean_squared_error: 0.0111
Epoch 42/50
Epoch 00041: val_loss did not improve
1s - loss: 0.0109 - acc: 0.5251 - mean_squared_error: 0.0109 - val_loss: 0.0111 - val_acc: 0.6963 - val_mean_squared_error: 0.0111
Epoch 43/50
Epoch 00042: val_loss improved from 0.01110 to 0.01096, saving model to ./model/SGD_model.weights.best.hdf5
1s - loss: 0.0108 - acc: 0.5380 - mean_squared_error: 0.0108 - val_loss: 0.0110 - val_acc: 0.6963 - val_mean_squared_error: 0.0110
Epoch 44/50
Epoch 00043: val_loss improved from 0.01096 to 0.01089, saving model to ./model/SGD_model.weights.best.hdf5
1s - loss: 0.0107 - acc: 0.5339 - mean_squared_error: 0.0107 - val_loss: 0.0109 - val_acc: 0.6963 - val_mean_squared_error: 0.0109
Epoch 45/50
Epoch 00044: val_loss improved from 0.01089 to 0.01086, saving model to ./model/SGD_model.weights.best.hdf5
1s - loss: 0.0107 - acc: 0.5234 - mean_squared_error: 0.0107 - val_loss: 0.0109 - val_acc: 0.6963 - val_mean_squared_error: 0.0109
Epoch 46/50
Epoch 00045: val_loss did not improve
1s - loss: 0.0106 - acc: 0.5321 - mean_squared_error: 0.0106 - val_loss: 0.0111 - val_acc: 0.6963 - val_mean_squared_error: 0.0111
Epoch 47/50
Epoch 00046: val_loss did not improve
1s - loss: 0.0105 - acc: 0.5333 - mean_squared_error: 0.0105 - val_loss: 0.0109 - val_acc: 0.6963 - val_mean_squared_error: 0.0109
Epoch 48/50
Epoch 00047: val_loss did not improve
1s - loss: 0.0103 - acc: 0.5228 - mean_squared_error: 0.0103 - val_loss: 0.0109 - val_acc: 0.6963 - val_mean_squared_error: 0.0109
Epoch 49/50
Epoch 00048: val_loss improved from 0.01086 to 0.01055, saving model to ./model/SGD_model.weights.best.hdf5
1s - loss: 0.0105 - acc: 0.5386 - mean_squared_error: 0.0105 - val_loss: 0.0106 - val_acc: 0.6963 - val_mean_squared_error: 0.0106
Epoch 50/50
Epoch 00049: val_loss improved from 0.01055 to 0.01042, saving model to ./model/SGD_model.weights.best.hdf5
1s - loss: 0.0104 - acc: 0.5187 - mean_squared_error: 0.0104 - val_loss: 0.0104 - val_acc: 0.6963 - val_mean_squared_error: 0.0104
Running model: dropout_base_model w/opt: RMSprop
Train on 1712 samples, validate on 428 samples
Epoch 1/50
Epoch 00000: val_loss improved from inf to 0.06051, saving model to ./model/RMSprop_model.weights.best.hdf5
3s - loss: 0.1892 - acc: 0.4019 - mean_squared_error: 0.1892 - val_loss: 0.0605 - val_acc: 0.6963 - val_mean_squared_error: 0.0605
Epoch 2/50
Epoch 00001: val_loss improved from 0.06051 to 0.01994, saving model to ./model/RMSprop_model.weights.best.hdf5
1s - loss: 0.0223 - acc: 0.4609 - mean_squared_error: 0.0223 - val_loss: 0.0199 - val_acc: 0.6963 - val_mean_squared_error: 0.0199
Epoch 3/50
Epoch 00002: val_loss improved from 0.01994 to 0.01546, saving model to ./model/RMSprop_model.weights.best.hdf5
1s - loss: 0.0134 - acc: 0.5491 - mean_squared_error: 0.0134 - val_loss: 0.0155 - val_acc: 0.6963 - val_mean_squared_error: 0.0155
Epoch 4/50
Epoch 00003: val_loss improved from 0.01546 to 0.00537, saving model to ./model/RMSprop_model.weights.best.hdf5
1s - loss: 0.0092 - acc: 0.5958 - mean_squared_error: 0.0092 - val_loss: 0.0054 - val_acc: 0.6963 - val_mean_squared_error: 0.0054
Epoch 5/50
Epoch 00004: val_loss did not improve
1s - loss: 0.0077 - acc: 0.6355 - mean_squared_error: 0.0077 - val_loss: 0.0081 - val_acc: 0.6963 - val_mean_squared_error: 0.0081
Epoch 6/50
Epoch 00005: val_loss improved from 0.00537 to 0.00511, saving model to ./model/RMSprop_model.weights.best.hdf5
1s - loss: 0.0067 - acc: 0.6560 - mean_squared_error: 0.0067 - val_loss: 0.0051 - val_acc: 0.6963 - val_mean_squared_error: 0.0051
Epoch 7/50
Epoch 00006: val_loss did not improve
1s - loss: 0.0058 - acc: 0.6624 - mean_squared_error: 0.0058 - val_loss: 0.0054 - val_acc: 0.6986 - val_mean_squared_error: 0.0054
Epoch 8/50
Epoch 00007: val_loss improved from 0.00511 to 0.00442, saving model to ./model/RMSprop_model.weights.best.hdf5
1s - loss: 0.0058 - acc: 0.6840 - mean_squared_error: 0.0058 - val_loss: 0.0044 - val_acc: 0.6963 - val_mean_squared_error: 0.0044
Epoch 9/50
Epoch 00008: val_loss improved from 0.00442 to 0.00325, saving model to ./model/RMSprop_model.weights.best.hdf5
1s - loss: 0.0052 - acc: 0.6869 - mean_squared_error: 0.0052 - val_loss: 0.0033 - val_acc: 0.6986 - val_mean_squared_error: 0.0033
Epoch 10/50
Epoch 00009: val_loss improved from 0.00325 to 0.00313, saving model to ./model/RMSprop_model.weights.best.hdf5
1s - loss: 0.0047 - acc: 0.6793 - mean_squared_error: 0.0047 - val_loss: 0.0031 - val_acc: 0.7103 - val_mean_squared_error: 0.0031
Epoch 11/50
Epoch 00010: val_loss improved from 0.00313 to 0.00295, saving model to ./model/RMSprop_model.weights.best.hdf5
1s - loss: 0.0044 - acc: 0.7050 - mean_squared_error: 0.0044 - val_loss: 0.0030 - val_acc: 0.7103 - val_mean_squared_error: 0.0030
Epoch 12/50
Epoch 00011: val_loss did not improve
1s - loss: 0.0041 - acc: 0.6992 - mean_squared_error: 0.0041 - val_loss: 0.0042 - val_acc: 0.7103 - val_mean_squared_error: 0.0042
Epoch 13/50
Epoch 00012: val_loss did not improve
1s - loss: 0.0038 - acc: 0.7109 - mean_squared_error: 0.0038 - val_loss: 0.0044 - val_acc: 0.7196 - val_mean_squared_error: 0.0044
Epoch 14/50
Epoch 00013: val_loss improved from 0.00295 to 0.00215, saving model to ./model/RMSprop_model.weights.best.hdf5
1s - loss: 0.0037 - acc: 0.7097 - mean_squared_error: 0.0037 - val_loss: 0.0022 - val_acc: 0.7150 - val_mean_squared_error: 0.0022
Epoch 15/50
Epoch 00014: val_loss did not improve
1s - loss: 0.0035 - acc: 0.7120 - mean_squared_error: 0.0035 - val_loss: 0.0022 - val_acc: 0.7150 - val_mean_squared_error: 0.0022
Epoch 16/50
Epoch 00015: val_loss did not improve
1s - loss: 0.0033 - acc: 0.7091 - mean_squared_error: 0.0033 - val_loss: 0.0028 - val_acc: 0.7103 - val_mean_squared_error: 0.0028
Epoch 17/50
Epoch 00016: val_loss did not improve
1s - loss: 0.0031 - acc: 0.7284 - mean_squared_error: 0.0031 - val_loss: 0.0041 - val_acc: 0.7103 - val_mean_squared_error: 0.0041
Epoch 18/50
Epoch 00017: val_loss did not improve
1s - loss: 0.0029 - acc: 0.7044 - mean_squared_error: 0.0029 - val_loss: 0.0037 - val_acc: 0.7103 - val_mean_squared_error: 0.0037
Epoch 19/50
Epoch 00018: val_loss improved from 0.00215 to 0.00173, saving model to ./model/RMSprop_model.weights.best.hdf5
1s - loss: 0.0027 - acc: 0.7301 - mean_squared_error: 0.0027 - val_loss: 0.0017 - val_acc: 0.7220 - val_mean_squared_error: 0.0017
Epoch 20/50
Epoch 00019: val_loss did not improve
1s - loss: 0.0025 - acc: 0.7243 - mean_squared_error: 0.0025 - val_loss: 0.0023 - val_acc: 0.7173 - val_mean_squared_error: 0.0023
Epoch 21/50
Epoch 00020: val_loss did not improve
1s - loss: 0.0025 - acc: 0.7249 - mean_squared_error: 0.0025 - val_loss: 0.0020 - val_acc: 0.7243 - val_mean_squared_error: 0.0020
Epoch 22/50
Epoch 00021: val_loss did not improve
1s - loss: 0.0023 - acc: 0.7173 - mean_squared_error: 0.0023 - val_loss: 0.0021 - val_acc: 0.7103 - val_mean_squared_error: 0.0021
Epoch 23/50
Epoch 00022: val_loss did not improve
1s - loss: 0.0023 - acc: 0.7190 - mean_squared_error: 0.0023 - val_loss: 0.0020 - val_acc: 0.7150 - val_mean_squared_error: 0.0020
Epoch 24/50
Epoch 00023: val_loss improved from 0.00173 to 0.00157, saving model to ./model/RMSprop_model.weights.best.hdf5
1s - loss: 0.0023 - acc: 0.7307 - mean_squared_error: 0.0023 - val_loss: 0.0016 - val_acc: 0.7266 - val_mean_squared_error: 0.0016
Epoch 25/50
Epoch 00024: val_loss did not improve
1s - loss: 0.0022 - acc: 0.7377 - mean_squared_error: 0.0022 - val_loss: 0.0017 - val_acc: 0.7150 - val_mean_squared_error: 0.0017
Epoch 26/50
Epoch 00025: val_loss did not improve
1s - loss: 0.0021 - acc: 0.7301 - mean_squared_error: 0.0021 - val_loss: 0.0018 - val_acc: 0.7220 - val_mean_squared_error: 0.0018
Epoch 27/50
Epoch 00026: val_loss improved from 0.00157 to 0.00149, saving model to ./model/RMSprop_model.weights.best.hdf5
1s - loss: 0.0021 - acc: 0.7383 - mean_squared_error: 0.0021 - val_loss: 0.0015 - val_acc: 0.7126 - val_mean_squared_error: 0.0015
Epoch 28/50
Epoch 00027: val_loss did not improve
1s - loss: 0.0020 - acc: 0.7354 - mean_squared_error: 0.0020 - val_loss: 0.0017 - val_acc: 0.7196 - val_mean_squared_error: 0.0017
Epoch 29/50
Epoch 00028: val_loss did not improve
1s - loss: 0.0019 - acc: 0.7307 - mean_squared_error: 0.0019 - val_loss: 0.0016 - val_acc: 0.7243 - val_mean_squared_error: 0.0016
Epoch 30/50
Epoch 00029: val_loss improved from 0.00149 to 0.00146, saving model to ./model/RMSprop_model.weights.best.hdf5
1s - loss: 0.0019 - acc: 0.7465 - mean_squared_error: 0.0019 - val_loss: 0.0015 - val_acc: 0.7220 - val_mean_squared_error: 0.0015
Epoch 31/50
Epoch 00030: val_loss did not improve
1s - loss: 0.0019 - acc: 0.7360 - mean_squared_error: 0.0019 - val_loss: 0.0015 - val_acc: 0.7383 - val_mean_squared_error: 0.0015
Epoch 32/50
Epoch 00031: val_loss did not improve
1s - loss: 0.0018 - acc: 0.7442 - mean_squared_error: 0.0018 - val_loss: 0.0017 - val_acc: 0.7290 - val_mean_squared_error: 0.0017
Epoch 33/50
Epoch 00032: val_loss did not improve
1s - loss: 0.0018 - acc: 0.7383 - mean_squared_error: 0.0018 - val_loss: 0.0020 - val_acc: 0.7150 - val_mean_squared_error: 0.0020
Epoch 34/50
Epoch 00033: val_loss improved from 0.00146 to 0.00140, saving model to ./model/RMSprop_model.weights.best.hdf5
1s - loss: 0.0017 - acc: 0.7482 - mean_squared_error: 0.0017 - val_loss: 0.0014 - val_acc: 0.7453 - val_mean_squared_error: 0.0014
Epoch 35/50
Epoch 00034: val_loss did not improve
1s - loss: 0.0017 - acc: 0.7389 - mean_squared_error: 0.0017 - val_loss: 0.0015 - val_acc: 0.7617 - val_mean_squared_error: 0.0015
Epoch 36/50
Epoch 00035: val_loss improved from 0.00140 to 0.00132, saving model to ./model/RMSprop_model.weights.best.hdf5
1s - loss: 0.0016 - acc: 0.7634 - mean_squared_error: 0.0016 - val_loss: 0.0013 - val_acc: 0.7593 - val_mean_squared_error: 0.0013
Epoch 37/50
Epoch 00036: val_loss improved from 0.00132 to 0.00129, saving model to ./model/RMSprop_model.weights.best.hdf5
1s - loss: 0.0015 - acc: 0.7558 - mean_squared_error: 0.0015 - val_loss: 0.0013 - val_acc: 0.7477 - val_mean_squared_error: 0.0013
Epoch 38/50
Epoch 00037: val_loss did not improve
1s - loss: 0.0015 - acc: 0.7652 - mean_squared_error: 0.0015 - val_loss: 0.0015 - val_acc: 0.7664 - val_mean_squared_error: 0.0015
Epoch 39/50
Epoch 00038: val_loss did not improve
1s - loss: 0.0016 - acc: 0.7681 - mean_squared_error: 0.0016 - val_loss: 0.0018 - val_acc: 0.7547 - val_mean_squared_error: 0.0018
Epoch 40/50
Epoch 00039: val_loss improved from 0.00129 to 0.00128, saving model to ./model/RMSprop_model.weights.best.hdf5
1s - loss: 0.0015 - acc: 0.7634 - mean_squared_error: 0.0015 - val_loss: 0.0013 - val_acc: 0.7664 - val_mean_squared_error: 0.0013
Epoch 41/50
Epoch 00040: val_loss did not improve
1s - loss: 0.0015 - acc: 0.7716 - mean_squared_error: 0.0015 - val_loss: 0.0013 - val_acc: 0.7710 - val_mean_squared_error: 0.0013
Epoch 42/50
Epoch 00041: val_loss did not improve
1s - loss: 0.0014 - acc: 0.7617 - mean_squared_error: 0.0014 - val_loss: 0.0014 - val_acc: 0.7664 - val_mean_squared_error: 0.0014
Epoch 43/50
Epoch 00042: val_loss did not improve
1s - loss: 0.0014 - acc: 0.7605 - mean_squared_error: 0.0014 - val_loss: 0.0019 - val_acc: 0.7734 - val_mean_squared_error: 0.0019
Epoch 44/50
Epoch 00043: val_loss improved from 0.00128 to 0.00119, saving model to ./model/RMSprop_model.weights.best.hdf5
1s - loss: 0.0014 - acc: 0.7810 - mean_squared_error: 0.0014 - val_loss: 0.0012 - val_acc: 0.7640 - val_mean_squared_error: 0.0012
Epoch 45/50
Epoch 00044: val_loss did not improve
1s - loss: 0.0013 - acc: 0.7827 - mean_squared_error: 0.0013 - val_loss: 0.0015 - val_acc: 0.7710 - val_mean_squared_error: 0.0015
Epoch 46/50
Epoch 00045: val_loss did not improve
1s - loss: 0.0013 - acc: 0.7921 - mean_squared_error: 0.0013 - val_loss: 0.0013 - val_acc: 0.7804 - val_mean_squared_error: 0.0013
Epoch 47/50
Epoch 00046: val_loss did not improve
1s - loss: 0.0013 - acc: 0.7769 - mean_squared_error: 0.0013 - val_loss: 0.0017 - val_acc: 0.7850 - val_mean_squared_error: 0.0017
Epoch 48/50
Epoch 00047: val_loss did not improve
1s - loss: 0.0013 - acc: 0.7827 - mean_squared_error: 0.0013 - val_loss: 0.0014 - val_acc: 0.7710 - val_mean_squared_error: 0.0014
Epoch 49/50
Epoch 00048: val_loss improved from 0.00119 to 0.00117, saving model to ./model/RMSprop_model.weights.best.hdf5
1s - loss: 0.0013 - acc: 0.7973 - mean_squared_error: 0.0013 - val_loss: 0.0012 - val_acc: 0.7967 - val_mean_squared_error: 0.0012
Epoch 50/50
Epoch 00049: val_loss did not improve
1s - loss: 0.0012 - acc: 0.7862 - mean_squared_error: 0.0012 - val_loss: 0.0012 - val_acc: 0.7827 - val_mean_squared_error: 0.0012
Running model: dropout_base_model w/opt: Adagrad
Train on 1712 samples, validate on 428 samples
Epoch 1/50
Epoch 00000: val_loss improved from inf to 0.03809, saving model to ./model/Adagrad_model.weights.best.hdf5
3s - loss: 1.3187 - acc: 0.3236 - mean_squared_error: 1.3187 - val_loss: 0.0381 - val_acc: 0.6963 - val_mean_squared_error: 0.0381
Epoch 2/50
Epoch 00001: val_loss improved from 0.03809 to 0.03041, saving model to ./model/Adagrad_model.weights.best.hdf5
1s - loss: 0.0169 - acc: 0.4626 - mean_squared_error: 0.0169 - val_loss: 0.0304 - val_acc: 0.6963 - val_mean_squared_error: 0.0304
Epoch 3/50
Epoch 00002: val_loss improved from 0.03041 to 0.02420, saving model to ./model/Adagrad_model.weights.best.hdf5
1s - loss: 0.0141 - acc: 0.4690 - mean_squared_error: 0.0141 - val_loss: 0.0242 - val_acc: 0.6963 - val_mean_squared_error: 0.0242
Epoch 4/50
Epoch 00003: val_loss improved from 0.02420 to 0.02176, saving model to ./model/Adagrad_model.weights.best.hdf5
1s - loss: 0.0128 - acc: 0.5058 - mean_squared_error: 0.0128 - val_loss: 0.0218 - val_acc: 0.6963 - val_mean_squared_error: 0.0218
Epoch 5/50
Epoch 00004: val_loss did not improve
1s - loss: 0.0122 - acc: 0.5222 - mean_squared_error: 0.0122 - val_loss: 0.0253 - val_acc: 0.6963 - val_mean_squared_error: 0.0253
Epoch 6/50
Epoch 00005: val_loss did not improve
1s - loss: 0.0117 - acc: 0.5327 - mean_squared_error: 0.0117 - val_loss: 0.0280 - val_acc: 0.6963 - val_mean_squared_error: 0.0280
Epoch 7/50
Epoch 00006: val_loss did not improve
1s - loss: 0.0111 - acc: 0.5257 - mean_squared_error: 0.0111 - val_loss: 0.0243 - val_acc: 0.6963 - val_mean_squared_error: 0.0243
Epoch 8/50
Epoch 00007: val_loss did not improve
1s - loss: 0.0108 - acc: 0.5397 - mean_squared_error: 0.0108 - val_loss: 0.0253 - val_acc: 0.6963 - val_mean_squared_error: 0.0253
Epoch 9/50
Epoch 00008: val_loss did not improve
1s - loss: 0.0106 - acc: 0.5695 - mean_squared_error: 0.0106 - val_loss: 0.0235 - val_acc: 0.6963 - val_mean_squared_error: 0.0235
Epoch 10/50
Epoch 00009: val_loss improved from 0.02176 to 0.01870, saving model to ./model/Adagrad_model.weights.best.hdf5
1s - loss: 0.0102 - acc: 0.5496 - mean_squared_error: 0.0102 - val_loss: 0.0187 - val_acc: 0.6963 - val_mean_squared_error: 0.0187
Epoch 11/50
Epoch 00010: val_loss did not improve
1s - loss: 0.0101 - acc: 0.5794 - mean_squared_error: 0.0101 - val_loss: 0.0247 - val_acc: 0.6963 - val_mean_squared_error: 0.0247
Epoch 12/50
Epoch 00011: val_loss did not improve
1s - loss: 0.0099 - acc: 0.5952 - mean_squared_error: 0.0099 - val_loss: 0.0241 - val_acc: 0.6963 - val_mean_squared_error: 0.0241
Epoch 13/50
Epoch 00012: val_loss did not improve
1s - loss: 0.0097 - acc: 0.5724 - mean_squared_error: 0.0097 - val_loss: 0.0215 - val_acc: 0.6963 - val_mean_squared_error: 0.0215
Epoch 14/50
Epoch 00013: val_loss did not improve
1s - loss: 0.0098 - acc: 0.5800 - mean_squared_error: 0.0098 - val_loss: 0.0213 - val_acc: 0.6963 - val_mean_squared_error: 0.0213
Epoch 15/50
Epoch 00014: val_loss did not improve
1s - loss: 0.0095 - acc: 0.5794 - mean_squared_error: 0.0095 - val_loss: 0.0213 - val_acc: 0.6963 - val_mean_squared_error: 0.0213
Epoch 16/50
Epoch 00015: val_loss did not improve
1s - loss: 0.0092 - acc: 0.5754 - mean_squared_error: 0.0092 - val_loss: 0.0233 - val_acc: 0.6963 - val_mean_squared_error: 0.0233
Epoch 17/50
Epoch 00016: val_loss improved from 0.01870 to 0.01725, saving model to ./model/Adagrad_model.weights.best.hdf5
1s - loss: 0.0092 - acc: 0.5882 - mean_squared_error: 0.0092 - val_loss: 0.0172 - val_acc: 0.6963 - val_mean_squared_error: 0.0172
Epoch 18/50
Epoch 00017: val_loss did not improve
1s - loss: 0.0089 - acc: 0.6063 - mean_squared_error: 0.0089 - val_loss: 0.0191 - val_acc: 0.6963 - val_mean_squared_error: 0.0191
Epoch 19/50
Epoch 00018: val_loss did not improve
1s - loss: 0.0091 - acc: 0.6110 - mean_squared_error: 0.0091 - val_loss: 0.0205 - val_acc: 0.6963 - val_mean_squared_error: 0.0205
Epoch 20/50
Epoch 00019: val_loss did not improve
1s - loss: 0.0089 - acc: 0.5853 - mean_squared_error: 0.0089 - val_loss: 0.0218 - val_acc: 0.6963 - val_mean_squared_error: 0.0218
Epoch 21/50
Epoch 00020: val_loss did not improve
1s - loss: 0.0089 - acc: 0.5987 - mean_squared_error: 0.0089 - val_loss: 0.0237 - val_acc: 0.6963 - val_mean_squared_error: 0.0237
Epoch 22/50
Epoch 00021: val_loss did not improve
1s - loss: 0.0088 - acc: 0.6192 - mean_squared_error: 0.0088 - val_loss: 0.0222 - val_acc: 0.6963 - val_mean_squared_error: 0.0222
Epoch 23/50
Epoch 00022: val_loss did not improve
1s - loss: 0.0087 - acc: 0.6051 - mean_squared_error: 0.0087 - val_loss: 0.0176 - val_acc: 0.6963 - val_mean_squared_error: 0.0176
Epoch 24/50
Epoch 00023: val_loss did not improve
1s - loss: 0.0089 - acc: 0.6151 - mean_squared_error: 0.0089 - val_loss: 0.0175 - val_acc: 0.6963 - val_mean_squared_error: 0.0175
Epoch 25/50
Epoch 00024: val_loss did not improve
1s - loss: 0.0087 - acc: 0.6268 - mean_squared_error: 0.0087 - val_loss: 0.0192 - val_acc: 0.6963 - val_mean_squared_error: 0.0192
Epoch 26/50
Epoch 00025: val_loss did not improve
1s - loss: 0.0088 - acc: 0.6238 - mean_squared_error: 0.0088 - val_loss: 0.0182 - val_acc: 0.6963 - val_mean_squared_error: 0.0182
Epoch 27/50
Epoch 00026: val_loss did not improve
1s - loss: 0.0086 - acc: 0.6262 - mean_squared_error: 0.0086 - val_loss: 0.0183 - val_acc: 0.6963 - val_mean_squared_error: 0.0183
Epoch 28/50
Epoch 00027: val_loss improved from 0.01725 to 0.01683, saving model to ./model/Adagrad_model.weights.best.hdf5
1s - loss: 0.0086 - acc: 0.6268 - mean_squared_error: 0.0086 - val_loss: 0.0168 - val_acc: 0.6963 - val_mean_squared_error: 0.0168
Epoch 29/50
Epoch 00028: val_loss improved from 0.01683 to 0.01537, saving model to ./model/Adagrad_model.weights.best.hdf5
1s - loss: 0.0086 - acc: 0.6192 - mean_squared_error: 0.0086 - val_loss: 0.0154 - val_acc: 0.6963 - val_mean_squared_error: 0.0154
Epoch 30/50
Epoch 00029: val_loss did not improve
1s - loss: 0.0084 - acc: 0.6168 - mean_squared_error: 0.0084 - val_loss: 0.0162 - val_acc: 0.6963 - val_mean_squared_error: 0.0162
Epoch 31/50
Epoch 00030: val_loss improved from 0.01537 to 0.01503, saving model to ./model/Adagrad_model.weights.best.hdf5
1s - loss: 0.0082 - acc: 0.6379 - mean_squared_error: 0.0082 - val_loss: 0.0150 - val_acc: 0.6963 - val_mean_squared_error: 0.0150
Epoch 32/50
Epoch 00031: val_loss did not improve
1s - loss: 0.0082 - acc: 0.6203 - mean_squared_error: 0.0082 - val_loss: 0.0167 - val_acc: 0.6963 - val_mean_squared_error: 0.0167
Epoch 33/50
Epoch 00032: val_loss did not improve
1s - loss: 0.0081 - acc: 0.6262 - mean_squared_error: 0.0081 - val_loss: 0.0173 - val_acc: 0.6963 - val_mean_squared_error: 0.0173
Epoch 34/50
Epoch 00033: val_loss did not improve
1s - loss: 0.0082 - acc: 0.6273 - mean_squared_error: 0.0082 - val_loss: 0.0156 - val_acc: 0.6963 - val_mean_squared_error: 0.0156
Epoch 35/50
Epoch 00034: val_loss did not improve
1s - loss: 0.0082 - acc: 0.6285 - mean_squared_error: 0.0082 - val_loss: 0.0185 - val_acc: 0.6963 - val_mean_squared_error: 0.0185
Epoch 36/50
Epoch 00035: val_loss did not improve
1s - loss: 0.0081 - acc: 0.6373 - mean_squared_error: 0.0081 - val_loss: 0.0163 - val_acc: 0.6963 - val_mean_squared_error: 0.0163
Epoch 37/50
Epoch 00036: val_loss did not improve
1s - loss: 0.0080 - acc: 0.6519 - mean_squared_error: 0.0080 - val_loss: 0.0164 - val_acc: 0.6963 - val_mean_squared_error: 0.0164
Epoch 38/50
Epoch 00037: val_loss improved from 0.01503 to 0.01263, saving model to ./model/Adagrad_model.weights.best.hdf5
1s - loss: 0.0078 - acc: 0.6414 - mean_squared_error: 0.0078 - val_loss: 0.0126 - val_acc: 0.6963 - val_mean_squared_error: 0.0126
Epoch 39/50
Epoch 00038: val_loss did not improve
1s - loss: 0.0077 - acc: 0.6367 - mean_squared_error: 0.0077 - val_loss: 0.0150 - val_acc: 0.6963 - val_mean_squared_error: 0.0150
Epoch 40/50
Epoch 00039: val_loss did not improve
1s - loss: 0.0078 - acc: 0.6542 - mean_squared_error: 0.0078 - val_loss: 0.0147 - val_acc: 0.6963 - val_mean_squared_error: 0.0147
Epoch 41/50
Epoch 00040: val_loss did not improve
1s - loss: 0.0077 - acc: 0.6379 - mean_squared_error: 0.0077 - val_loss: 0.0176 - val_acc: 0.6963 - val_mean_squared_error: 0.0176
Epoch 42/50
Epoch 00041: val_loss did not improve
1s - loss: 0.0076 - acc: 0.6484 - mean_squared_error: 0.0076 - val_loss: 0.0138 - val_acc: 0.6986 - val_mean_squared_error: 0.0138
Epoch 43/50
Epoch 00042: val_loss did not improve
1s - loss: 0.0078 - acc: 0.6408 - mean_squared_error: 0.0078 - val_loss: 0.0139 - val_acc: 0.6963 - val_mean_squared_error: 0.0139
Epoch 44/50
Epoch 00043: val_loss did not improve
1s - loss: 0.0074 - acc: 0.6565 - mean_squared_error: 0.0074 - val_loss: 0.0149 - val_acc: 0.6986 - val_mean_squared_error: 0.0149
Epoch 45/50
Epoch 00044: val_loss improved from 0.01263 to 0.01204, saving model to ./model/Adagrad_model.weights.best.hdf5
1s - loss: 0.0076 - acc: 0.6460 - mean_squared_error: 0.0076 - val_loss: 0.0120 - val_acc: 0.6963 - val_mean_squared_error: 0.0120
Epoch 46/50
Epoch 00045: val_loss did not improve
1s - loss: 0.0076 - acc: 0.6641 - mean_squared_error: 0.0076 - val_loss: 0.0150 - val_acc: 0.6986 - val_mean_squared_error: 0.0150
Epoch 47/50
Epoch 00046: val_loss did not improve
1s - loss: 0.0073 - acc: 0.6332 - mean_squared_error: 0.0073 - val_loss: 0.0143 - val_acc: 0.6963 - val_mean_squared_error: 0.0143
Epoch 48/50
Epoch 00047: val_loss did not improve
1s - loss: 0.0072 - acc: 0.6507 - mean_squared_error: 0.0072 - val_loss: 0.0129 - val_acc: 0.6963 - val_mean_squared_error: 0.0129
Epoch 49/50
Epoch 00048: val_loss did not improve
1s - loss: 0.0069 - acc: 0.6542 - mean_squared_error: 0.0069 - val_loss: 0.0129 - val_acc: 0.6986 - val_mean_squared_error: 0.0129
Epoch 50/50
Epoch 00049: val_loss improved from 0.01204 to 0.01175, saving model to ./model/Adagrad_model.weights.best.hdf5
1s - loss: 0.0072 - acc: 0.6595 - mean_squared_error: 0.0072 - val_loss: 0.0117 - val_acc: 0.6986 - val_mean_squared_error: 0.0117
Running model: dropout_base_model w/opt: Adadelta
Train on 1712 samples, validate on 428 samples
Epoch 1/50
Epoch 00000: val_loss improved from inf to 0.01602, saving model to ./model/Adadelta_model.weights.best.hdf5
3s - loss: 0.0240 - acc: 0.4001 - mean_squared_error: 0.0240 - val_loss: 0.0160 - val_acc: 0.6963 - val_mean_squared_error: 0.0160
Epoch 2/50
Epoch 00001: val_loss did not improve
1s - loss: 0.0129 - acc: 0.5327 - mean_squared_error: 0.0129 - val_loss: 0.0190 - val_acc: 0.6963 - val_mean_squared_error: 0.0190
Epoch 3/50
Epoch 00002: val_loss improved from 0.01602 to 0.00796, saving model to ./model/Adadelta_model.weights.best.hdf5
1s - loss: 0.0105 - acc: 0.5444 - mean_squared_error: 0.0105 - val_loss: 0.0080 - val_acc: 0.6963 - val_mean_squared_error: 0.0080
Epoch 4/50
Epoch 00003: val_loss did not improve
1s - loss: 0.0091 - acc: 0.5847 - mean_squared_error: 0.0091 - val_loss: 0.0107 - val_acc: 0.6963 - val_mean_squared_error: 0.0107
Epoch 5/50
Epoch 00004: val_loss improved from 0.00796 to 0.00660, saving model to ./model/Adadelta_model.weights.best.hdf5
1s - loss: 0.0084 - acc: 0.5940 - mean_squared_error: 0.0084 - val_loss: 0.0066 - val_acc: 0.6963 - val_mean_squared_error: 0.0066
Epoch 6/50
Epoch 00005: val_loss did not improve
1s - loss: 0.0079 - acc: 0.6063 - mean_squared_error: 0.0079 - val_loss: 0.0150 - val_acc: 0.6963 - val_mean_squared_error: 0.0150
Epoch 7/50
Epoch 00006: val_loss did not improve
1s - loss: 0.0075 - acc: 0.6203 - mean_squared_error: 0.0075 - val_loss: 0.0085 - val_acc: 0.6963 - val_mean_squared_error: 0.0085
Epoch 8/50
Epoch 00007: val_loss did not improve
1s - loss: 0.0071 - acc: 0.6355 - mean_squared_error: 0.0071 - val_loss: 0.0095 - val_acc: 0.6963 - val_mean_squared_error: 0.0095
Epoch 9/50
Epoch 00008: val_loss did not improve
1s - loss: 0.0066 - acc: 0.6355 - mean_squared_error: 0.0066 - val_loss: 0.0074 - val_acc: 0.6963 - val_mean_squared_error: 0.0074
Epoch 10/50
Epoch 00009: val_loss did not improve
1s - loss: 0.0065 - acc: 0.6513 - mean_squared_error: 0.0065 - val_loss: 0.0087 - val_acc: 0.6963 - val_mean_squared_error: 0.0087
Epoch 11/50
Epoch 00010: val_loss improved from 0.00660 to 0.00658, saving model to ./model/Adadelta_model.weights.best.hdf5
1s - loss: 0.0062 - acc: 0.6495 - mean_squared_error: 0.0062 - val_loss: 0.0066 - val_acc: 0.6963 - val_mean_squared_error: 0.0066
Epoch 12/50
Epoch 00011: val_loss did not improve
1s - loss: 0.0062 - acc: 0.6700 - mean_squared_error: 0.0062 - val_loss: 0.0099 - val_acc: 0.6963 - val_mean_squared_error: 0.0099
Epoch 13/50
Epoch 00012: val_loss did not improve
1s - loss: 0.0060 - acc: 0.6676 - mean_squared_error: 0.0060 - val_loss: 0.0101 - val_acc: 0.6963 - val_mean_squared_error: 0.0101
Epoch 14/50
Epoch 00013: val_loss did not improve
1s - loss: 0.0058 - acc: 0.6711 - mean_squared_error: 0.0058 - val_loss: 0.0090 - val_acc: 0.6963 - val_mean_squared_error: 0.0090
Epoch 15/50
Epoch 00014: val_loss did not improve
1s - loss: 0.0056 - acc: 0.6875 - mean_squared_error: 0.0056 - val_loss: 0.0072 - val_acc: 0.6963 - val_mean_squared_error: 0.0072
Epoch 16/50
Epoch 00015: val_loss did not improve
1s - loss: 0.0055 - acc: 0.6770 - mean_squared_error: 0.0055 - val_loss: 0.0085 - val_acc: 0.6963 - val_mean_squared_error: 0.0085
Epoch 17/50
Epoch 00016: val_loss did not improve
1s - loss: 0.0055 - acc: 0.6828 - mean_squared_error: 0.0055 - val_loss: 0.0071 - val_acc: 0.6963 - val_mean_squared_error: 0.0071
Epoch 18/50
Epoch 00017: val_loss improved from 0.00658 to 0.00634, saving model to ./model/Adadelta_model.weights.best.hdf5
1s - loss: 0.0054 - acc: 0.6904 - mean_squared_error: 0.0054 - val_loss: 0.0063 - val_acc: 0.6963 - val_mean_squared_error: 0.0063
Epoch 19/50
Epoch 00018: val_loss improved from 0.00634 to 0.00618, saving model to ./model/Adadelta_model.weights.best.hdf5
1s - loss: 0.0052 - acc: 0.6805 - mean_squared_error: 0.0052 - val_loss: 0.0062 - val_acc: 0.6963 - val_mean_squared_error: 0.0062
Epoch 20/50
Epoch 00019: val_loss improved from 0.00618 to 0.00442, saving model to ./model/Adadelta_model.weights.best.hdf5
1s - loss: 0.0051 - acc: 0.6834 - mean_squared_error: 0.0051 - val_loss: 0.0044 - val_acc: 0.6963 - val_mean_squared_error: 0.0044
Epoch 21/50
Epoch 00020: val_loss did not improve
1s - loss: 0.0051 - acc: 0.6881 - mean_squared_error: 0.0051 - val_loss: 0.0047 - val_acc: 0.6963 - val_mean_squared_error: 0.0047
Epoch 22/50
Epoch 00021: val_loss did not improve
1s - loss: 0.0050 - acc: 0.6875 - mean_squared_error: 0.0050 - val_loss: 0.0073 - val_acc: 0.6963 - val_mean_squared_error: 0.0073
Epoch 23/50
Epoch 00022: val_loss did not improve
1s - loss: 0.0049 - acc: 0.6968 - mean_squared_error: 0.0049 - val_loss: 0.0047 - val_acc: 0.6963 - val_mean_squared_error: 0.0047
Epoch 24/50
Epoch 00023: val_loss did not improve
1s - loss: 0.0048 - acc: 0.6957 - mean_squared_error: 0.0048 - val_loss: 0.0059 - val_acc: 0.6963 - val_mean_squared_error: 0.0059
Epoch 25/50
Epoch 00024: val_loss did not improve
1s - loss: 0.0047 - acc: 0.6945 - mean_squared_error: 0.0047 - val_loss: 0.0052 - val_acc: 0.6963 - val_mean_squared_error: 0.0052
Epoch 26/50
Epoch 00025: val_loss did not improve
1s - loss: 0.0047 - acc: 0.7039 - mean_squared_error: 0.0047 - val_loss: 0.0046 - val_acc: 0.6963 - val_mean_squared_error: 0.0046
Epoch 27/50
Epoch 00026: val_loss did not improve
1s - loss: 0.0046 - acc: 0.7004 - mean_squared_error: 0.0046 - val_loss: 0.0046 - val_acc: 0.6963 - val_mean_squared_error: 0.0046
Epoch 28/50
Epoch 00027: val_loss did not improve
1s - loss: 0.0045 - acc: 0.6933 - mean_squared_error: 0.0045 - val_loss: 0.0049 - val_acc: 0.6963 - val_mean_squared_error: 0.0049
Epoch 29/50
Epoch 00028: val_loss improved from 0.00442 to 0.00439, saving model to ./model/Adadelta_model.weights.best.hdf5
1s - loss: 0.0045 - acc: 0.6992 - mean_squared_error: 0.0045 - val_loss: 0.0044 - val_acc: 0.6963 - val_mean_squared_error: 0.0044
Epoch 30/50
Epoch 00029: val_loss did not improve
1s - loss: 0.0043 - acc: 0.6957 - mean_squared_error: 0.0043 - val_loss: 0.0048 - val_acc: 0.6963 - val_mean_squared_error: 0.0048
Epoch 31/50
Epoch 00030: val_loss improved from 0.00439 to 0.00433, saving model to ./model/Adadelta_model.weights.best.hdf5
1s - loss: 0.0042 - acc: 0.6957 - mean_squared_error: 0.0042 - val_loss: 0.0043 - val_acc: 0.6963 - val_mean_squared_error: 0.0043
Epoch 32/50
Epoch 00031: val_loss did not improve
1s - loss: 0.0042 - acc: 0.6951 - mean_squared_error: 0.0042 - val_loss: 0.0045 - val_acc: 0.6963 - val_mean_squared_error: 0.0045
Epoch 33/50
Epoch 00032: val_loss improved from 0.00433 to 0.00375, saving model to ./model/Adadelta_model.weights.best.hdf5
1s - loss: 0.0041 - acc: 0.6998 - mean_squared_error: 0.0041 - val_loss: 0.0038 - val_acc: 0.6963 - val_mean_squared_error: 0.0038
Epoch 34/50
Epoch 00033: val_loss did not improve
1s - loss: 0.0041 - acc: 0.6974 - mean_squared_error: 0.0041 - val_loss: 0.0043 - val_acc: 0.6963 - val_mean_squared_error: 0.0043
Epoch 35/50
Epoch 00034: val_loss did not improve
1s - loss: 0.0040 - acc: 0.7015 - mean_squared_error: 0.0040 - val_loss: 0.0046 - val_acc: 0.6963 - val_mean_squared_error: 0.0046
Epoch 36/50
Epoch 00035: val_loss did not improve
1s - loss: 0.0039 - acc: 0.7021 - mean_squared_error: 0.0039 - val_loss: 0.0047 - val_acc: 0.6963 - val_mean_squared_error: 0.0047
Epoch 37/50
Epoch 00036: val_loss did not improve
1s - loss: 0.0039 - acc: 0.7050 - mean_squared_error: 0.0039 - val_loss: 0.0038 - val_acc: 0.6963 - val_mean_squared_error: 0.0038
Epoch 38/50
Epoch 00037: val_loss did not improve
1s - loss: 0.0038 - acc: 0.7132 - mean_squared_error: 0.0038 - val_loss: 0.0057 - val_acc: 0.7009 - val_mean_squared_error: 0.0057
Epoch 39/50
Epoch 00038: val_loss did not improve
1s - loss: 0.0038 - acc: 0.7062 - mean_squared_error: 0.0038 - val_loss: 0.0038 - val_acc: 0.6963 - val_mean_squared_error: 0.0038
Epoch 40/50
Epoch 00039: val_loss improved from 0.00375 to 0.00362, saving model to ./model/Adadelta_model.weights.best.hdf5
1s - loss: 0.0037 - acc: 0.6980 - mean_squared_error: 0.0037 - val_loss: 0.0036 - val_acc: 0.6986 - val_mean_squared_error: 0.0036
Epoch 41/50
Epoch 00040: val_loss did not improve
1s - loss: 0.0036 - acc: 0.7085 - mean_squared_error: 0.0036 - val_loss: 0.0042 - val_acc: 0.7009 - val_mean_squared_error: 0.0042
Epoch 42/50
Epoch 00041: val_loss improved from 0.00362 to 0.00357, saving model to ./model/Adadelta_model.weights.best.hdf5
1s - loss: 0.0036 - acc: 0.6939 - mean_squared_error: 0.0036 - val_loss: 0.0036 - val_acc: 0.7009 - val_mean_squared_error: 0.0036
Epoch 43/50
Epoch 00042: val_loss improved from 0.00357 to 0.00344, saving model to ./model/Adadelta_model.weights.best.hdf5
1s - loss: 0.0035 - acc: 0.7085 - mean_squared_error: 0.0035 - val_loss: 0.0034 - val_acc: 0.7009 - val_mean_squared_error: 0.0034
Epoch 44/50
Epoch 00043: val_loss did not improve
1s - loss: 0.0034 - acc: 0.6986 - mean_squared_error: 0.0034 - val_loss: 0.0038 - val_acc: 0.7009 - val_mean_squared_error: 0.0038
Epoch 45/50
Epoch 00044: val_loss improved from 0.00344 to 0.00302, saving model to ./model/Adadelta_model.weights.best.hdf5
1s - loss: 0.0034 - acc: 0.7009 - mean_squared_error: 0.0034 - val_loss: 0.0030 - val_acc: 0.7009 - val_mean_squared_error: 0.0030
Epoch 46/50
Epoch 00045: val_loss improved from 0.00302 to 0.00281, saving model to ./model/Adadelta_model.weights.best.hdf5
1s - loss: 0.0033 - acc: 0.7009 - mean_squared_error: 0.0033 - val_loss: 0.0028 - val_acc: 0.7009 - val_mean_squared_error: 0.0028
Epoch 47/50
Epoch 00046: val_loss did not improve
1s - loss: 0.0034 - acc: 0.6957 - mean_squared_error: 0.0034 - val_loss: 0.0028 - val_acc: 0.7009 - val_mean_squared_error: 0.0028
Epoch 48/50
Epoch 00047: val_loss did not improve
1s - loss: 0.0033 - acc: 0.7015 - mean_squared_error: 0.0033 - val_loss: 0.0029 - val_acc: 0.6986 - val_mean_squared_error: 0.0029
Epoch 49/50
Epoch 00048: val_loss did not improve
1s - loss: 0.0032 - acc: 0.7004 - mean_squared_error: 0.0032 - val_loss: 0.0031 - val_acc: 0.7009 - val_mean_squared_error: 0.0031
Epoch 50/50
Epoch 00049: val_loss did not improve
1s - loss: 0.0032 - acc: 0.7097 - mean_squared_error: 0.0032 - val_loss: 0.0029 - val_acc: 0.7009 - val_mean_squared_error: 0.0029
Running model: dropout_base_model w/opt: Adam
Train on 1712 samples, validate on 428 samples
Epoch 1/50
Epoch 00000: val_loss improved from inf to 0.07780, saving model to ./model/Adam_model.weights.best.hdf5
3s - loss: 0.0630 - acc: 0.2845 - mean_squared_error: 0.0630 - val_loss: 0.0778 - val_acc: 0.6822 - val_mean_squared_error: 0.0778
Epoch 2/50
Epoch 00001: val_loss improved from 0.07780 to 0.05070, saving model to ./model/Adam_model.weights.best.hdf5
1s - loss: 0.0158 - acc: 0.4322 - mean_squared_error: 0.0158 - val_loss: 0.0507 - val_acc: 0.6682 - val_mean_squared_error: 0.0507
Epoch 3/50
Epoch 00002: val_loss did not improve
1s - loss: 0.0116 - acc: 0.5111 - mean_squared_error: 0.0116 - val_loss: 0.0520 - val_acc: 0.6963 - val_mean_squared_error: 0.0520
Epoch 4/50
Epoch 00003: val_loss improved from 0.05070 to 0.04590, saving model to ./model/Adam_model.weights.best.hdf5
1s - loss: 0.0098 - acc: 0.5432 - mean_squared_error: 0.0098 - val_loss: 0.0459 - val_acc: 0.6963 - val_mean_squared_error: 0.0459
Epoch 5/50
Epoch 00004: val_loss improved from 0.04590 to 0.03359, saving model to ./model/Adam_model.weights.best.hdf5
1s - loss: 0.0091 - acc: 0.5724 - mean_squared_error: 0.0091 - val_loss: 0.0336 - val_acc: 0.6963 - val_mean_squared_error: 0.0336
Epoch 6/50
Epoch 00005: val_loss did not improve
1s - loss: 0.0081 - acc: 0.6016 - mean_squared_error: 0.0081 - val_loss: 0.0362 - val_acc: 0.6986 - val_mean_squared_error: 0.0362
Epoch 7/50
Epoch 00006: val_loss improved from 0.03359 to 0.02460, saving model to ./model/Adam_model.weights.best.hdf5
1s - loss: 0.0078 - acc: 0.6121 - mean_squared_error: 0.0078 - val_loss: 0.0246 - val_acc: 0.6963 - val_mean_squared_error: 0.0246
Epoch 8/50
Epoch 00007: val_loss improved from 0.02460 to 0.02105, saving model to ./model/Adam_model.weights.best.hdf5
1s - loss: 0.0073 - acc: 0.6414 - mean_squared_error: 0.0073 - val_loss: 0.0211 - val_acc: 0.6963 - val_mean_squared_error: 0.0211
Epoch 9/50
Epoch 00008: val_loss improved from 0.02105 to 0.01922, saving model to ./model/Adam_model.weights.best.hdf5
2s - loss: 0.0068 - acc: 0.6530 - mean_squared_error: 0.0068 - val_loss: 0.0192 - val_acc: 0.6986 - val_mean_squared_error: 0.0192
Epoch 10/50
Epoch 00009: val_loss did not improve
1s - loss: 0.0065 - acc: 0.6454 - mean_squared_error: 0.0065 - val_loss: 0.0207 - val_acc: 0.6963 - val_mean_squared_error: 0.0207
Epoch 11/50
Epoch 00010: val_loss improved from 0.01922 to 0.01819, saving model to ./model/Adam_model.weights.best.hdf5
1s - loss: 0.0062 - acc: 0.6647 - mean_squared_error: 0.0062 - val_loss: 0.0182 - val_acc: 0.6963 - val_mean_squared_error: 0.0182
Epoch 12/50
Epoch 00011: val_loss improved from 0.01819 to 0.01432, saving model to ./model/Adam_model.weights.best.hdf5
1s - loss: 0.0061 - acc: 0.6612 - mean_squared_error: 0.0061 - val_loss: 0.0143 - val_acc: 0.6986 - val_mean_squared_error: 0.0143
Epoch 13/50
Epoch 00012: val_loss improved from 0.01432 to 0.01276, saving model to ./model/Adam_model.weights.best.hdf5
1s - loss: 0.0058 - acc: 0.6817 - mean_squared_error: 0.0058 - val_loss: 0.0128 - val_acc: 0.6963 - val_mean_squared_error: 0.0128
Epoch 14/50
Epoch 00013: val_loss did not improve
1s - loss: 0.0056 - acc: 0.7033 - mean_squared_error: 0.0056 - val_loss: 0.0130 - val_acc: 0.6986 - val_mean_squared_error: 0.0130
Epoch 15/50
Epoch 00014: val_loss improved from 0.01276 to 0.01033, saving model to ./model/Adam_model.weights.best.hdf5
1s - loss: 0.0054 - acc: 0.6974 - mean_squared_error: 0.0054 - val_loss: 0.0103 - val_acc: 0.6963 - val_mean_squared_error: 0.0103
Epoch 16/50
Epoch 00015: val_loss did not improve
1s - loss: 0.0052 - acc: 0.6957 - mean_squared_error: 0.0052 - val_loss: 0.0112 - val_acc: 0.6963 - val_mean_squared_error: 0.0112
Epoch 17/50
Epoch 00016: val_loss improved from 0.01033 to 0.00748, saving model to ./model/Adam_model.weights.best.hdf5
1s - loss: 0.0050 - acc: 0.7056 - mean_squared_error: 0.0050 - val_loss: 0.0075 - val_acc: 0.6963 - val_mean_squared_error: 0.0075
Epoch 18/50
Epoch 00017: val_loss improved from 0.00748 to 0.00620, saving model to ./model/Adam_model.weights.best.hdf5
1s - loss: 0.0049 - acc: 0.7091 - mean_squared_error: 0.0049 - val_loss: 0.0062 - val_acc: 0.7009 - val_mean_squared_error: 0.0062
Epoch 19/50
Epoch 00018: val_loss improved from 0.00620 to 0.00617, saving model to ./model/Adam_model.weights.best.hdf5
1s - loss: 0.0046 - acc: 0.7120 - mean_squared_error: 0.0046 - val_loss: 0.0062 - val_acc: 0.6986 - val_mean_squared_error: 0.0062
Epoch 20/50
Epoch 00019: val_loss improved from 0.00617 to 0.00565, saving model to ./model/Adam_model.weights.best.hdf5
1s - loss: 0.0045 - acc: 0.7091 - mean_squared_error: 0.0045 - val_loss: 0.0057 - val_acc: 0.7009 - val_mean_squared_error: 0.0057
Epoch 21/50
Epoch 00020: val_loss improved from 0.00565 to 0.00533, saving model to ./model/Adam_model.weights.best.hdf5
1s - loss: 0.0043 - acc: 0.7009 - mean_squared_error: 0.0043 - val_loss: 0.0053 - val_acc: 0.7033 - val_mean_squared_error: 0.0053
Epoch 22/50
Epoch 00021: val_loss improved from 0.00533 to 0.00463, saving model to ./model/Adam_model.weights.best.hdf5
1s - loss: 0.0042 - acc: 0.7068 - mean_squared_error: 0.0042 - val_loss: 0.0046 - val_acc: 0.7056 - val_mean_squared_error: 0.0046
Epoch 23/50
Epoch 00022: val_loss improved from 0.00463 to 0.00410, saving model to ./model/Adam_model.weights.best.hdf5
1s - loss: 0.0041 - acc: 0.7039 - mean_squared_error: 0.0041 - val_loss: 0.0041 - val_acc: 0.7056 - val_mean_squared_error: 0.0041
Epoch 24/50
Epoch 00023: val_loss improved from 0.00410 to 0.00368, saving model to ./model/Adam_model.weights.best.hdf5
1s - loss: 0.0039 - acc: 0.7097 - mean_squared_error: 0.0039 - val_loss: 0.0037 - val_acc: 0.7033 - val_mean_squared_error: 0.0037
Epoch 25/50
Epoch 00024: val_loss improved from 0.00368 to 0.00317, saving model to ./model/Adam_model.weights.best.hdf5
1s - loss: 0.0038 - acc: 0.7074 - mean_squared_error: 0.0038 - val_loss: 0.0032 - val_acc: 0.7009 - val_mean_squared_error: 0.0032
Epoch 26/50
Epoch 00025: val_loss did not improve
1s - loss: 0.0037 - acc: 0.7044 - mean_squared_error: 0.0037 - val_loss: 0.0036 - val_acc: 0.7056 - val_mean_squared_error: 0.0036
Epoch 27/50
Epoch 00026: val_loss improved from 0.00317 to 0.00315, saving model to ./model/Adam_model.weights.best.hdf5
1s - loss: 0.0036 - acc: 0.7103 - mean_squared_error: 0.0036 - val_loss: 0.0031 - val_acc: 0.7079 - val_mean_squared_error: 0.0031
Epoch 28/50
Epoch 00027: val_loss improved from 0.00315 to 0.00286, saving model to ./model/Adam_model.weights.best.hdf5
1s - loss: 0.0035 - acc: 0.7132 - mean_squared_error: 0.0035 - val_loss: 0.0029 - val_acc: 0.7079 - val_mean_squared_error: 0.0029
Epoch 29/50
Epoch 00028: val_loss improved from 0.00286 to 0.00267, saving model to ./model/Adam_model.weights.best.hdf5
2s - loss: 0.0033 - acc: 0.7044 - mean_squared_error: 0.0033 - val_loss: 0.0027 - val_acc: 0.7056 - val_mean_squared_error: 0.0027
Epoch 30/50
Epoch 00029: val_loss improved from 0.00267 to 0.00258, saving model to ./model/Adam_model.weights.best.hdf5
1s - loss: 0.0032 - acc: 0.7126 - mean_squared_error: 0.0032 - val_loss: 0.0026 - val_acc: 0.7103 - val_mean_squared_error: 0.0026
Epoch 31/50
Epoch 00030: val_loss improved from 0.00258 to 0.00257, saving model to ./model/Adam_model.weights.best.hdf5
1s - loss: 0.0032 - acc: 0.7068 - mean_squared_error: 0.0032 - val_loss: 0.0026 - val_acc: 0.7150 - val_mean_squared_error: 0.0026
Epoch 32/50
Epoch 00031: val_loss improved from 0.00257 to 0.00232, saving model to ./model/Adam_model.weights.best.hdf5
1s - loss: 0.0031 - acc: 0.7214 - mean_squared_error: 0.0031 - val_loss: 0.0023 - val_acc: 0.7079 - val_mean_squared_error: 0.0023
Epoch 33/50
Epoch 00032: val_loss improved from 0.00232 to 0.00229, saving model to ./model/Adam_model.weights.best.hdf5
1s - loss: 0.0030 - acc: 0.7202 - mean_squared_error: 0.0030 - val_loss: 0.0023 - val_acc: 0.7103 - val_mean_squared_error: 0.0023
Epoch 34/50
Epoch 00033: val_loss did not improve
1s - loss: 0.0029 - acc: 0.7027 - mean_squared_error: 0.0029 - val_loss: 0.0024 - val_acc: 0.6986 - val_mean_squared_error: 0.0024
Epoch 35/50
Epoch 00034: val_loss did not improve
1s - loss: 0.0029 - acc: 0.7114 - mean_squared_error: 0.0029 - val_loss: 0.0024 - val_acc: 0.7079 - val_mean_squared_error: 0.0024
Epoch 36/50
Epoch 00035: val_loss improved from 0.00229 to 0.00213, saving model to ./model/Adam_model.weights.best.hdf5
1s - loss: 0.0028 - acc: 0.7190 - mean_squared_error: 0.0028 - val_loss: 0.0021 - val_acc: 0.7056 - val_mean_squared_error: 0.0021
Epoch 37/50
Epoch 00036: val_loss did not improve
1s - loss: 0.0027 - acc: 0.7173 - mean_squared_error: 0.0027 - val_loss: 0.0022 - val_acc: 0.7243 - val_mean_squared_error: 0.0022
Epoch 38/50
Epoch 00037: val_loss improved from 0.00213 to 0.00200, saving model to ./model/Adam_model.weights.best.hdf5
1s - loss: 0.0026 - acc: 0.7161 - mean_squared_error: 0.0026 - val_loss: 0.0020 - val_acc: 0.7056 - val_mean_squared_error: 0.0020
Epoch 39/50
Epoch 00038: val_loss did not improve
1s - loss: 0.0026 - acc: 0.7325 - mean_squared_error: 0.0026 - val_loss: 0.0021 - val_acc: 0.7126 - val_mean_squared_error: 0.0021
Epoch 40/50
Epoch 00039: val_loss improved from 0.00200 to 0.00193, saving model to ./model/Adam_model.weights.best.hdf5
1s - loss: 0.0025 - acc: 0.7208 - mean_squared_error: 0.0025 - val_loss: 0.0019 - val_acc: 0.7150 - val_mean_squared_error: 0.0019
Epoch 41/50
Epoch 00040: val_loss improved from 0.00193 to 0.00190, saving model to ./model/Adam_model.weights.best.hdf5
1s - loss: 0.0025 - acc: 0.7261 - mean_squared_error: 0.0025 - val_loss: 0.0019 - val_acc: 0.7150 - val_mean_squared_error: 0.0019
Epoch 42/50
Epoch 00041: val_loss improved from 0.00190 to 0.00186, saving model to ./model/Adam_model.weights.best.hdf5
1s - loss: 0.0024 - acc: 0.7313 - mean_squared_error: 0.0024 - val_loss: 0.0019 - val_acc: 0.7126 - val_mean_squared_error: 0.0019
Epoch 43/50
Epoch 00042: val_loss did not improve
1s - loss: 0.0024 - acc: 0.7313 - mean_squared_error: 0.0024 - val_loss: 0.0019 - val_acc: 0.7079 - val_mean_squared_error: 0.0019
Epoch 44/50
Epoch 00043: val_loss improved from 0.00186 to 0.00185, saving model to ./model/Adam_model.weights.best.hdf5
1s - loss: 0.0023 - acc: 0.7249 - mean_squared_error: 0.0023 - val_loss: 0.0018 - val_acc: 0.7196 - val_mean_squared_error: 0.0018
Epoch 45/50
Epoch 00044: val_loss did not improve
1s - loss: 0.0023 - acc: 0.7319 - mean_squared_error: 0.0023 - val_loss: 0.0019 - val_acc: 0.7220 - val_mean_squared_error: 0.0019
Epoch 46/50
Epoch 00045: val_loss improved from 0.00185 to 0.00181, saving model to ./model/Adam_model.weights.best.hdf5
1s - loss: 0.0022 - acc: 0.7249 - mean_squared_error: 0.0022 - val_loss: 0.0018 - val_acc: 0.7290 - val_mean_squared_error: 0.0018
Epoch 47/50
Epoch 00046: val_loss improved from 0.00181 to 0.00171, saving model to ./model/Adam_model.weights.best.hdf5
1s - loss: 0.0022 - acc: 0.7278 - mean_squared_error: 0.0022 - val_loss: 0.0017 - val_acc: 0.7220 - val_mean_squared_error: 0.0017
Epoch 48/50
Epoch 00047: val_loss improved from 0.00171 to 0.00169, saving model to ./model/Adam_model.weights.best.hdf5
1s - loss: 0.0021 - acc: 0.7354 - mean_squared_error: 0.0021 - val_loss: 0.0017 - val_acc: 0.7266 - val_mean_squared_error: 0.0017
Epoch 49/50
Epoch 00048: val_loss did not improve
1s - loss: 0.0021 - acc: 0.7424 - mean_squared_error: 0.0021 - val_loss: 0.0017 - val_acc: 0.7313 - val_mean_squared_error: 0.0017
Epoch 50/50
Epoch 00049: val_loss improved from 0.00169 to 0.00166, saving model to ./model/Adam_model.weights.best.hdf5
1s - loss: 0.0021 - acc: 0.7296 - mean_squared_error: 0.0021 - val_loss: 0.0017 - val_acc: 0.7407 - val_mean_squared_error: 0.0017
Running model: dropout_base_model w/opt: Adamax
Train on 1712 samples, validate on 428 samples
Epoch 1/50
Epoch 00000: val_loss improved from inf to 0.03776, saving model to ./model/Adamax_model.weights.best.hdf5
3s - loss: 0.0297 - acc: 0.4188 - mean_squared_error: 0.0297 - val_loss: 0.0378 - val_acc: 0.6963 - val_mean_squared_error: 0.0378
Epoch 2/50
Epoch 00001: val_loss improved from 0.03776 to 0.02951, saving model to ./model/Adamax_model.weights.best.hdf5
1s - loss: 0.0114 - acc: 0.5362 - mean_squared_error: 0.0114 - val_loss: 0.0295 - val_acc: 0.6963 - val_mean_squared_error: 0.0295
Epoch 3/50
Epoch 00002: val_loss improved from 0.02951 to 0.02418, saving model to ./model/Adamax_model.weights.best.hdf5
1s - loss: 0.0089 - acc: 0.5970 - mean_squared_error: 0.0089 - val_loss: 0.0242 - val_acc: 0.6963 - val_mean_squared_error: 0.0242
Epoch 4/50
Epoch 00003: val_loss improved from 0.02418 to 0.01630, saving model to ./model/Adamax_model.weights.best.hdf5
1s - loss: 0.0080 - acc: 0.6092 - mean_squared_error: 0.0080 - val_loss: 0.0163 - val_acc: 0.6963 - val_mean_squared_error: 0.0163
Epoch 5/50
Epoch 00004: val_loss did not improve
1s - loss: 0.0076 - acc: 0.6402 - mean_squared_error: 0.0076 - val_loss: 0.0171 - val_acc: 0.6963 - val_mean_squared_error: 0.0171
Epoch 6/50
Epoch 00005: val_loss improved from 0.01630 to 0.01461, saving model to ./model/Adamax_model.weights.best.hdf5
1s - loss: 0.0067 - acc: 0.6624 - mean_squared_error: 0.0067 - val_loss: 0.0146 - val_acc: 0.6963 - val_mean_squared_error: 0.0146
Epoch 7/50
Epoch 00006: val_loss improved from 0.01461 to 0.01217, saving model to ./model/Adamax_model.weights.best.hdf5
1s - loss: 0.0063 - acc: 0.6507 - mean_squared_error: 0.0063 - val_loss: 0.0122 - val_acc: 0.6963 - val_mean_squared_error: 0.0122
Epoch 8/50
Epoch 00007: val_loss improved from 0.01217 to 0.01011, saving model to ./model/Adamax_model.weights.best.hdf5
1s - loss: 0.0058 - acc: 0.6700 - mean_squared_error: 0.0058 - val_loss: 0.0101 - val_acc: 0.7056 - val_mean_squared_error: 0.0101
Epoch 9/50
Epoch 00008: val_loss did not improve
1s - loss: 0.0055 - acc: 0.6700 - mean_squared_error: 0.0055 - val_loss: 0.0115 - val_acc: 0.7009 - val_mean_squared_error: 0.0115
Epoch 10/50
Epoch 00009: val_loss did not improve
1s - loss: 0.0053 - acc: 0.6612 - mean_squared_error: 0.0053 - val_loss: 0.0110 - val_acc: 0.7173 - val_mean_squared_error: 0.0110
Epoch 11/50
Epoch 00010: val_loss improved from 0.01011 to 0.00741, saving model to ./model/Adamax_model.weights.best.hdf5
1s - loss: 0.0051 - acc: 0.6752 - mean_squared_error: 0.0051 - val_loss: 0.0074 - val_acc: 0.7033 - val_mean_squared_error: 0.0074
Epoch 12/50
Epoch 00011: val_loss improved from 0.00741 to 0.00719, saving model to ./model/Adamax_model.weights.best.hdf5
1s - loss: 0.0049 - acc: 0.6735 - mean_squared_error: 0.0049 - val_loss: 0.0072 - val_acc: 0.7126 - val_mean_squared_error: 0.0072
Epoch 13/50
Epoch 00012: val_loss improved from 0.00719 to 0.00588, saving model to ./model/Adamax_model.weights.best.hdf5
1s - loss: 0.0046 - acc: 0.6641 - mean_squared_error: 0.0046 - val_loss: 0.0059 - val_acc: 0.7243 - val_mean_squared_error: 0.0059
Epoch 14/50
Epoch 00013: val_loss did not improve
1s - loss: 0.0045 - acc: 0.6834 - mean_squared_error: 0.0045 - val_loss: 0.0096 - val_acc: 0.7173 - val_mean_squared_error: 0.0096
Epoch 15/50
Epoch 00014: val_loss improved from 0.00588 to 0.00504, saving model to ./model/Adamax_model.weights.best.hdf5
1s - loss: 0.0044 - acc: 0.6904 - mean_squared_error: 0.0044 - val_loss: 0.0050 - val_acc: 0.7079 - val_mean_squared_error: 0.0050
Epoch 16/50
Epoch 00015: val_loss did not improve
1s - loss: 0.0043 - acc: 0.6922 - mean_squared_error: 0.0043 - val_loss: 0.0053 - val_acc: 0.7150 - val_mean_squared_error: 0.0053
Epoch 17/50
Epoch 00016: val_loss improved from 0.00504 to 0.00438, saving model to ./model/Adamax_model.weights.best.hdf5
1s - loss: 0.0039 - acc: 0.6893 - mean_squared_error: 0.0039 - val_loss: 0.0044 - val_acc: 0.7056 - val_mean_squared_error: 0.0044
Epoch 18/50
Epoch 00017: val_loss did not improve
1s - loss: 0.0041 - acc: 0.6822 - mean_squared_error: 0.0041 - val_loss: 0.0056 - val_acc: 0.7079 - val_mean_squared_error: 0.0056
Epoch 19/50
Epoch 00018: val_loss improved from 0.00438 to 0.00361, saving model to ./model/Adamax_model.weights.best.hdf5
1s - loss: 0.0038 - acc: 0.7091 - mean_squared_error: 0.0038 - val_loss: 0.0036 - val_acc: 0.7126 - val_mean_squared_error: 0.0036
Epoch 20/50
Epoch 00019: val_loss did not improve
1s - loss: 0.0037 - acc: 0.6980 - mean_squared_error: 0.0037 - val_loss: 0.0053 - val_acc: 0.7336 - val_mean_squared_error: 0.0053
Epoch 21/50
Epoch 00020: val_loss did not improve
1s - loss: 0.0037 - acc: 0.7091 - mean_squared_error: 0.0037 - val_loss: 0.0063 - val_acc: 0.7290 - val_mean_squared_error: 0.0063
Epoch 22/50
Epoch 00021: val_loss improved from 0.00361 to 0.00325, saving model to ./model/Adamax_model.weights.best.hdf5
1s - loss: 0.0036 - acc: 0.6910 - mean_squared_error: 0.0036 - val_loss: 0.0032 - val_acc: 0.7266 - val_mean_squared_error: 0.0032
Epoch 23/50
Epoch 00022: val_loss improved from 0.00325 to 0.00308, saving model to ./model/Adamax_model.weights.best.hdf5
1s - loss: 0.0034 - acc: 0.7091 - mean_squared_error: 0.0034 - val_loss: 0.0031 - val_acc: 0.7126 - val_mean_squared_error: 0.0031
Epoch 24/50
Epoch 00023: val_loss improved from 0.00308 to 0.00279, saving model to ./model/Adamax_model.weights.best.hdf5
1s - loss: 0.0034 - acc: 0.7056 - mean_squared_error: 0.0034 - val_loss: 0.0028 - val_acc: 0.7383 - val_mean_squared_error: 0.0028
Epoch 25/50
Epoch 00024: val_loss did not improve
1s - loss: 0.0033 - acc: 0.7155 - mean_squared_error: 0.0033 - val_loss: 0.0041 - val_acc: 0.7266 - val_mean_squared_error: 0.0041
Epoch 26/50
Epoch 00025: val_loss did not improve
1s - loss: 0.0032 - acc: 0.7208 - mean_squared_error: 0.0032 - val_loss: 0.0032 - val_acc: 0.7150 - val_mean_squared_error: 0.0032
Epoch 27/50
Epoch 00026: val_loss did not improve
1s - loss: 0.0032 - acc: 0.7155 - mean_squared_error: 0.0032 - val_loss: 0.0030 - val_acc: 0.7243 - val_mean_squared_error: 0.0030
Epoch 28/50
Epoch 00027: val_loss improved from 0.00279 to 0.00199, saving model to ./model/Adamax_model.weights.best.hdf5
1s - loss: 0.0031 - acc: 0.7114 - mean_squared_error: 0.0031 - val_loss: 0.0020 - val_acc: 0.7266 - val_mean_squared_error: 0.0020
Epoch 29/50
Epoch 00028: val_loss did not improve
1s - loss: 0.0031 - acc: 0.7266 - mean_squared_error: 0.0031 - val_loss: 0.0026 - val_acc: 0.7266 - val_mean_squared_error: 0.0026
Epoch 30/50
Epoch 00029: val_loss did not improve
1s - loss: 0.0030 - acc: 0.7144 - mean_squared_error: 0.0030 - val_loss: 0.0029 - val_acc: 0.7243 - val_mean_squared_error: 0.0029
Epoch 31/50
Epoch 00030: val_loss did not improve
1s - loss: 0.0029 - acc: 0.7383 - mean_squared_error: 0.0029 - val_loss: 0.0032 - val_acc: 0.7243 - val_mean_squared_error: 0.0032
Epoch 32/50
Epoch 00031: val_loss did not improve
1s - loss: 0.0028 - acc: 0.7196 - mean_squared_error: 0.0028 - val_loss: 0.0024 - val_acc: 0.7196 - val_mean_squared_error: 0.0024
Epoch 33/50
Epoch 00032: val_loss did not improve
1s - loss: 0.0027 - acc: 0.7103 - mean_squared_error: 0.0027 - val_loss: 0.0029 - val_acc: 0.7336 - val_mean_squared_error: 0.0029
Epoch 34/50
Epoch 00033: val_loss did not improve
1s - loss: 0.0027 - acc: 0.7266 - mean_squared_error: 0.0027 - val_loss: 0.0021 - val_acc: 0.7336 - val_mean_squared_error: 0.0021
Epoch 35/50
Epoch 00034: val_loss improved from 0.00199 to 0.00188, saving model to ./model/Adamax_model.weights.best.hdf5
1s - loss: 0.0026 - acc: 0.7196 - mean_squared_error: 0.0026 - val_loss: 0.0019 - val_acc: 0.7360 - val_mean_squared_error: 0.0019
Epoch 36/50
Epoch 00035: val_loss did not improve
1s - loss: 0.0025 - acc: 0.7366 - mean_squared_error: 0.0025 - val_loss: 0.0026 - val_acc: 0.7336 - val_mean_squared_error: 0.0026
Epoch 37/50
Epoch 00036: val_loss improved from 0.00188 to 0.00160, saving model to ./model/Adamax_model.weights.best.hdf5
1s - loss: 0.0025 - acc: 0.7319 - mean_squared_error: 0.0025 - val_loss: 0.0016 - val_acc: 0.7336 - val_mean_squared_error: 0.0016
Epoch 38/50
Epoch 00037: val_loss did not improve
1s - loss: 0.0025 - acc: 0.7284 - mean_squared_error: 0.0025 - val_loss: 0.0018 - val_acc: 0.7313 - val_mean_squared_error: 0.0018
Epoch 39/50
Epoch 00038: val_loss did not improve
1s - loss: 0.0024 - acc: 0.7296 - mean_squared_error: 0.0024 - val_loss: 0.0022 - val_acc: 0.7313 - val_mean_squared_error: 0.0022
Epoch 40/50
Epoch 00039: val_loss did not improve
1s - loss: 0.0024 - acc: 0.7418 - mean_squared_error: 0.0024 - val_loss: 0.0024 - val_acc: 0.7430 - val_mean_squared_error: 0.0024
Epoch 41/50
Epoch 00040: val_loss did not improve
1s - loss: 0.0023 - acc: 0.7430 - mean_squared_error: 0.0023 - val_loss: 0.0018 - val_acc: 0.7313 - val_mean_squared_error: 0.0018
Epoch 42/50
Epoch 00041: val_loss did not improve
1s - loss: 0.0023 - acc: 0.7395 - mean_squared_error: 0.0023 - val_loss: 0.0016 - val_acc: 0.7313 - val_mean_squared_error: 0.0016
Epoch 43/50
Epoch 00042: val_loss did not improve
1s - loss: 0.0022 - acc: 0.7442 - mean_squared_error: 0.0022 - val_loss: 0.0019 - val_acc: 0.7313 - val_mean_squared_error: 0.0019
Epoch 44/50
Epoch 00043: val_loss did not improve
1s - loss: 0.0021 - acc: 0.7477 - mean_squared_error: 0.0021 - val_loss: 0.0017 - val_acc: 0.7313 - val_mean_squared_error: 0.0017
Epoch 45/50
Epoch 00044: val_loss did not improve
1s - loss: 0.0021 - acc: 0.7407 - mean_squared_error: 0.0021 - val_loss: 0.0017 - val_acc: 0.7336 - val_mean_squared_error: 0.0017
Epoch 46/50
Epoch 00045: val_loss did not improve
1s - loss: 0.0021 - acc: 0.7605 - mean_squared_error: 0.0021 - val_loss: 0.0018 - val_acc: 0.7336 - val_mean_squared_error: 0.0018
Epoch 47/50
Epoch 00046: val_loss did not improve
1s - loss: 0.0020 - acc: 0.7395 - mean_squared_error: 0.0020 - val_loss: 0.0019 - val_acc: 0.7430 - val_mean_squared_error: 0.0019
Epoch 48/50
Epoch 00047: val_loss improved from 0.00160 to 0.00156, saving model to ./model/Adamax_model.weights.best.hdf5
1s - loss: 0.0020 - acc: 0.7576 - mean_squared_error: 0.0020 - val_loss: 0.0016 - val_acc: 0.7383 - val_mean_squared_error: 0.0016
Epoch 49/50
Epoch 00048: val_loss did not improve
1s - loss: 0.0020 - acc: 0.7570 - mean_squared_error: 0.0020 - val_loss: 0.0018 - val_acc: 0.7477 - val_mean_squared_error: 0.0018
Epoch 50/50
Epoch 00049: val_loss improved from 0.00156 to 0.00137, saving model to ./model/Adamax_model.weights.best.hdf5
1s - loss: 0.0019 - acc: 0.7588 - mean_squared_error: 0.0019 - val_loss: 0.0014 - val_acc: 0.7570 - val_mean_squared_error: 0.0014
Running model: dropout_base_model w/opt: Nadam
Train on 1712 samples, validate on 428 samples
Epoch 1/50
Epoch 00000: val_loss improved from inf to 0.05018, saving model to ./model/Nadam_model.weights.best.hdf5
3s - loss: 0.1321 - acc: 0.2728 - mean_squared_error: 0.1321 - val_loss: 0.0502 - val_acc: 0.6963 - val_mean_squared_error: 0.0502
Epoch 2/50
Epoch 00001: val_loss improved from 0.05018 to 0.02929, saving model to ./model/Nadam_model.weights.best.hdf5
1s - loss: 0.0192 - acc: 0.4731 - mean_squared_error: 0.0192 - val_loss: 0.0293 - val_acc: 0.6963 - val_mean_squared_error: 0.0293
Epoch 3/50
Epoch 00002: val_loss did not improve
1s - loss: 0.0141 - acc: 0.5613 - mean_squared_error: 0.0141 - val_loss: 0.0379 - val_acc: 0.6963 - val_mean_squared_error: 0.0379
Epoch 4/50
Epoch 00003: val_loss improved from 0.02929 to 0.01899, saving model to ./model/Nadam_model.weights.best.hdf5
1s - loss: 0.0118 - acc: 0.6121 - mean_squared_error: 0.0118 - val_loss: 0.0190 - val_acc: 0.6963 - val_mean_squared_error: 0.0190
Epoch 5/50
Epoch 00004: val_loss did not improve
1s - loss: 0.0112 - acc: 0.6332 - mean_squared_error: 0.0112 - val_loss: 0.0206 - val_acc: 0.6963 - val_mean_squared_error: 0.0206
Epoch 6/50
Epoch 00005: val_loss improved from 0.01899 to 0.01631, saving model to ./model/Nadam_model.weights.best.hdf5
1s - loss: 0.0098 - acc: 0.6361 - mean_squared_error: 0.0098 - val_loss: 0.0163 - val_acc: 0.6963 - val_mean_squared_error: 0.0163
Epoch 7/50
Epoch 00006: val_loss did not improve
1s - loss: 0.0088 - acc: 0.6717 - mean_squared_error: 0.0088 - val_loss: 0.0210 - val_acc: 0.6963 - val_mean_squared_error: 0.0210
Epoch 8/50
Epoch 00007: val_loss did not improve
1s - loss: 0.0083 - acc: 0.6618 - mean_squared_error: 0.0083 - val_loss: 0.0170 - val_acc: 0.6963 - val_mean_squared_error: 0.0170
Epoch 9/50
Epoch 00008: val_loss improved from 0.01631 to 0.00938, saving model to ./model/Nadam_model.weights.best.hdf5
1s - loss: 0.0076 - acc: 0.6595 - mean_squared_error: 0.0076 - val_loss: 0.0094 - val_acc: 0.6963 - val_mean_squared_error: 0.0094
Epoch 10/50
Epoch 00009: val_loss did not improve
1s - loss: 0.0075 - acc: 0.6671 - mean_squared_error: 0.0075 - val_loss: 0.0096 - val_acc: 0.6963 - val_mean_squared_error: 0.0096
Epoch 11/50
Epoch 00010: val_loss did not improve
1s - loss: 0.0070 - acc: 0.6741 - mean_squared_error: 0.0070 - val_loss: 0.0116 - val_acc: 0.6963 - val_mean_squared_error: 0.0116
Epoch 12/50
Epoch 00011: val_loss did not improve
1s - loss: 0.0065 - acc: 0.6776 - mean_squared_error: 0.0065 - val_loss: 0.0094 - val_acc: 0.6963 - val_mean_squared_error: 0.0094
Epoch 13/50
Epoch 00012: val_loss did not improve
1s - loss: 0.0064 - acc: 0.6875 - mean_squared_error: 0.0064 - val_loss: 0.0100 - val_acc: 0.6963 - val_mean_squared_error: 0.0100
Epoch 14/50
Epoch 00013: val_loss improved from 0.00938 to 0.00739, saving model to ./model/Nadam_model.weights.best.hdf5
1s - loss: 0.0060 - acc: 0.6922 - mean_squared_error: 0.0060 - val_loss: 0.0074 - val_acc: 0.6963 - val_mean_squared_error: 0.0074
Epoch 15/50
Epoch 00014: val_loss did not improve
1s - loss: 0.0057 - acc: 0.6893 - mean_squared_error: 0.0057 - val_loss: 0.0081 - val_acc: 0.6963 - val_mean_squared_error: 0.0081
Epoch 16/50
Epoch 00015: val_loss improved from 0.00739 to 0.00610, saving model to ./model/Nadam_model.weights.best.hdf5
1s - loss: 0.0053 - acc: 0.6922 - mean_squared_error: 0.0053 - val_loss: 0.0061 - val_acc: 0.6963 - val_mean_squared_error: 0.0061
Epoch 17/50
Epoch 00016: val_loss improved from 0.00610 to 0.00522, saving model to ./model/Nadam_model.weights.best.hdf5
1s - loss: 0.0052 - acc: 0.6998 - mean_squared_error: 0.0052 - val_loss: 0.0052 - val_acc: 0.6963 - val_mean_squared_error: 0.0052
Epoch 18/50
Epoch 00017: val_loss did not improve
1s - loss: 0.0049 - acc: 0.6875 - mean_squared_error: 0.0049 - val_loss: 0.0054 - val_acc: 0.6963 - val_mean_squared_error: 0.0054
Epoch 19/50
Epoch 00018: val_loss improved from 0.00522 to 0.00520, saving model to ./model/Nadam_model.weights.best.hdf5
1s - loss: 0.0047 - acc: 0.6980 - mean_squared_error: 0.0047 - val_loss: 0.0052 - val_acc: 0.6963 - val_mean_squared_error: 0.0052
Epoch 20/50
Epoch 00019: val_loss improved from 0.00520 to 0.00488, saving model to ./model/Nadam_model.weights.best.hdf5
1s - loss: 0.0046 - acc: 0.6998 - mean_squared_error: 0.0046 - val_loss: 0.0049 - val_acc: 0.6963 - val_mean_squared_error: 0.0049
Epoch 21/50
Epoch 00020: val_loss improved from 0.00488 to 0.00453, saving model to ./model/Nadam_model.weights.best.hdf5
1s - loss: 0.0045 - acc: 0.6986 - mean_squared_error: 0.0045 - val_loss: 0.0045 - val_acc: 0.6963 - val_mean_squared_error: 0.0045
Epoch 22/50
Epoch 00021: val_loss improved from 0.00453 to 0.00400, saving model to ./model/Nadam_model.weights.best.hdf5
1s - loss: 0.0043 - acc: 0.7074 - mean_squared_error: 0.0043 - val_loss: 0.0040 - val_acc: 0.6963 - val_mean_squared_error: 0.0040
Epoch 23/50
Epoch 00022: val_loss improved from 0.00400 to 0.00386, saving model to ./model/Nadam_model.weights.best.hdf5
1s - loss: 0.0040 - acc: 0.7079 - mean_squared_error: 0.0040 - val_loss: 0.0039 - val_acc: 0.7033 - val_mean_squared_error: 0.0039
Epoch 24/50
Epoch 00023: val_loss improved from 0.00386 to 0.00316, saving model to ./model/Nadam_model.weights.best.hdf5
2s - loss: 0.0039 - acc: 0.7004 - mean_squared_error: 0.0039 - val_loss: 0.0032 - val_acc: 0.7033 - val_mean_squared_error: 0.0032
Epoch 25/50
Epoch 00024: val_loss did not improve
1s - loss: 0.0037 - acc: 0.6992 - mean_squared_error: 0.0037 - val_loss: 0.0032 - val_acc: 0.6963 - val_mean_squared_error: 0.0032
Epoch 26/50
Epoch 00025: val_loss improved from 0.00316 to 0.00304, saving model to ./model/Nadam_model.weights.best.hdf5
1s - loss: 0.0036 - acc: 0.7132 - mean_squared_error: 0.0036 - val_loss: 0.0030 - val_acc: 0.6986 - val_mean_squared_error: 0.0030
Epoch 27/50
Epoch 00026: val_loss improved from 0.00304 to 0.00292, saving model to ./model/Nadam_model.weights.best.hdf5
1s - loss: 0.0034 - acc: 0.7068 - mean_squared_error: 0.0034 - val_loss: 0.0029 - val_acc: 0.7056 - val_mean_squared_error: 0.0029
Epoch 28/50
Epoch 00027: val_loss did not improve
1s - loss: 0.0034 - acc: 0.7079 - mean_squared_error: 0.0034 - val_loss: 0.0031 - val_acc: 0.7056 - val_mean_squared_error: 0.0031
Epoch 29/50
Epoch 00028: val_loss improved from 0.00292 to 0.00281, saving model to ./model/Nadam_model.weights.best.hdf5
1s - loss: 0.0033 - acc: 0.7079 - mean_squared_error: 0.0033 - val_loss: 0.0028 - val_acc: 0.7009 - val_mean_squared_error: 0.0028
Epoch 30/50
Epoch 00029: val_loss improved from 0.00281 to 0.00266, saving model to ./model/Nadam_model.weights.best.hdf5
1s - loss: 0.0031 - acc: 0.7150 - mean_squared_error: 0.0031 - val_loss: 0.0027 - val_acc: 0.7009 - val_mean_squared_error: 0.0027
Epoch 31/50
Epoch 00030: val_loss did not improve
1s - loss: 0.0031 - acc: 0.7074 - mean_squared_error: 0.0031 - val_loss: 0.0027 - val_acc: 0.7079 - val_mean_squared_error: 0.0027
Epoch 32/50
Epoch 00031: val_loss improved from 0.00266 to 0.00263, saving model to ./model/Nadam_model.weights.best.hdf5
1s - loss: 0.0030 - acc: 0.7097 - mean_squared_error: 0.0030 - val_loss: 0.0026 - val_acc: 0.7009 - val_mean_squared_error: 0.0026
Epoch 33/50
Epoch 00032: val_loss improved from 0.00263 to 0.00260, saving model to ./model/Nadam_model.weights.best.hdf5
1s - loss: 0.0030 - acc: 0.7202 - mean_squared_error: 0.0030 - val_loss: 0.0026 - val_acc: 0.7009 - val_mean_squared_error: 0.0026
Epoch 34/50
Epoch 00033: val_loss improved from 0.00260 to 0.00244, saving model to ./model/Nadam_model.weights.best.hdf5
1s - loss: 0.0029 - acc: 0.7120 - mean_squared_error: 0.0029 - val_loss: 0.0024 - val_acc: 0.7056 - val_mean_squared_error: 0.0024
Epoch 35/50
Epoch 00034: val_loss did not improve
1s - loss: 0.0029 - acc: 0.7114 - mean_squared_error: 0.0029 - val_loss: 0.0025 - val_acc: 0.7056 - val_mean_squared_error: 0.0025
Epoch 36/50
Epoch 00035: val_loss improved from 0.00244 to 0.00231, saving model to ./model/Nadam_model.weights.best.hdf5
1s - loss: 0.0028 - acc: 0.7114 - mean_squared_error: 0.0028 - val_loss: 0.0023 - val_acc: 0.7033 - val_mean_squared_error: 0.0023
Epoch 37/50
Epoch 00036: val_loss did not improve
1s - loss: 0.0027 - acc: 0.7120 - mean_squared_error: 0.0027 - val_loss: 0.0024 - val_acc: 0.7009 - val_mean_squared_error: 0.0024
Epoch 38/50
Epoch 00037: val_loss improved from 0.00231 to 0.00228, saving model to ./model/Nadam_model.weights.best.hdf5
1s - loss: 0.0027 - acc: 0.7138 - mean_squared_error: 0.0027 - val_loss: 0.0023 - val_acc: 0.7079 - val_mean_squared_error: 0.0023
Epoch 39/50
Epoch 00038: val_loss did not improve
1s - loss: 0.0027 - acc: 0.7155 - mean_squared_error: 0.0027 - val_loss: 0.0024 - val_acc: 0.7056 - val_mean_squared_error: 0.0024
Epoch 40/50
Epoch 00039: val_loss did not improve
1s - loss: 0.0026 - acc: 0.7179 - mean_squared_error: 0.0026 - val_loss: 0.0023 - val_acc: 0.7056 - val_mean_squared_error: 0.0023
Epoch 41/50
Epoch 00040: val_loss improved from 0.00228 to 0.00220, saving model to ./model/Nadam_model.weights.best.hdf5
2s - loss: 0.0026 - acc: 0.7173 - mean_squared_error: 0.0026 - val_loss: 0.0022 - val_acc: 0.7079 - val_mean_squared_error: 0.0022
Epoch 42/50
Epoch 00041: val_loss improved from 0.00220 to 0.00219, saving model to ./model/Nadam_model.weights.best.hdf5
2s - loss: 0.0026 - acc: 0.7185 - mean_squared_error: 0.0026 - val_loss: 0.0022 - val_acc: 0.7056 - val_mean_squared_error: 0.0022
Epoch 43/50
Epoch 00042: val_loss improved from 0.00219 to 0.00215, saving model to ./model/Nadam_model.weights.best.hdf5
1s - loss: 0.0025 - acc: 0.7155 - mean_squared_error: 0.0025 - val_loss: 0.0021 - val_acc: 0.7056 - val_mean_squared_error: 0.0021
Epoch 44/50
Epoch 00043: val_loss improved from 0.00215 to 0.00210, saving model to ./model/Nadam_model.weights.best.hdf5
1s - loss: 0.0025 - acc: 0.7196 - mean_squared_error: 0.0025 - val_loss: 0.0021 - val_acc: 0.7079 - val_mean_squared_error: 0.0021
Epoch 45/50
Epoch 00044: val_loss did not improve
1s - loss: 0.0025 - acc: 0.7109 - mean_squared_error: 0.0025 - val_loss: 0.0022 - val_acc: 0.7033 - val_mean_squared_error: 0.0022
Epoch 46/50
Epoch 00045: val_loss improved from 0.00210 to 0.00202, saving model to ./model/Nadam_model.weights.best.hdf5
2s - loss: 0.0025 - acc: 0.7266 - mean_squared_error: 0.0025 - val_loss: 0.0020 - val_acc: 0.7079 - val_mean_squared_error: 0.0020
Epoch 47/50
Epoch 00046: val_loss did not improve
1s - loss: 0.0024 - acc: 0.7120 - mean_squared_error: 0.0024 - val_loss: 0.0021 - val_acc: 0.7033 - val_mean_squared_error: 0.0021
Epoch 48/50
Epoch 00047: val_loss improved from 0.00202 to 0.00201, saving model to ./model/Nadam_model.weights.best.hdf5
1s - loss: 0.0024 - acc: 0.7109 - mean_squared_error: 0.0024 - val_loss: 0.0020 - val_acc: 0.7079 - val_mean_squared_error: 0.0020
Epoch 49/50
Epoch 00048: val_loss improved from 0.00201 to 0.00195, saving model to ./model/Nadam_model.weights.best.hdf5
2s - loss: 0.0024 - acc: 0.7167 - mean_squared_error: 0.0024 - val_loss: 0.0020 - val_acc: 0.7033 - val_mean_squared_error: 0.0020
Epoch 50/50
Epoch 00049: val_loss improved from 0.00195 to 0.00193, saving model to ./model/Nadam_model.weights.best.hdf5
1s - loss: 0.0024 - acc: 0.7167 - mean_squared_error: 0.0024 - val_loss: 0.0019 - val_acc: 0.7056 - val_mean_squared_error: 0.0019